Total 5,279 Others data entry job vacancies in Hong Kong

Key Responsibilities: 

• Pre-sales support: Work closely with sales and delivery team to define, demonstrate, build solution and estimate for a potential opportunity. 

• Providing vision on industry trends and client challenges to develop compelling value propositions for prioritized industries 

• Developing Go-To-Market approaches for the Singapore/APAC Cluster across geographies and industries, aligned with NTT DATA Group’s Data & AI portfolio and offerings 

• Supporting the Sales League in identifying both target customers and relevant Data & AI solutions to enhance sales performance 

• Engaging in client discussions, identifying new opportunities, and driving them with Sales Teams 

• Augmenting Sales Teams for effective pre-sales activities (e.g., customer engagement pitches, solutioning, proposals) 

• Leveraging the most appropriate global capabilities (e.g., Centers of Excellence, Global Delivery Centers, and local practices), assets, delivery models, and methodologies to deliver optimal sales and delivery solutions 

• Differentiating NTT DATA’s Data & AI customer proposals through innovation, leveraging Group capabilities (e.g., AI Labs, Innovation Centres, Robotics Lab, Research Centres) 

• Bridging market demand with skill supply plans, contributing to the development of short- and long-term recruitment and reskilling strategies to support growth 

• Compiling and implementing development plans for Migration/upgrade of Data and AI platform. 

• Ability to guide the development team on the design, testing, and modification stages. 

Knowledge and Attributes: 

• At least 10 years of experience in consulting and/or IT services; 

• Having led data-driven projects with direct connection to business outcomes: data platform with modern technologies (Azure, AWS, Google, Snowflake, Databricks); data government projects (Informatica, Collibra, Azure Pureview); AI projects (Custom ML/AI models, Gen AI, Agentic AI); 

• Experienced in strategic selling of Data and AI solutions in Singapore. 

• Being talented to blend Business perspective and Technological solutions; 

• Relevant CxO relationships, preferably in Singapore, both towards business and IT stakeholders; 

• Knowledgeable of Data & AI market dynamics; 

• Fluent in English with excellent communication/oration skills. 

Academic Qualifications and Certifications: 

• Bachelor's degree or equivalent in information technology/systems or Equivalent. 

• Hands on experience in any of Data and AI platforms. 

• Prior Pre-sales experience with systems integration (SI) organization is preferred. 

Required experience: 

• Advanced track record as a developer and architect of new systems/solutions. 

• Advanced client engagement and development consulting experience. 

• Advanced experience managing expectations when balancing alternatives against business and financial constraints. 

• Advanced experience in a variety of architectures for specific domain or specialization. 

• Advanced designer and development know-how. 

• Advanced experience presenting technical solutions to non-technical audiences. 

• Advanced experience working in an agile development environment. 
  Having led data-driven projects with direct connection to business outcomes: data platform with modern technologies (Azure, AWS, Google, Snowflake, Databricks); data government projects (Informatica, Collibra, Azure Pureview); AI projects (Custom ML/AI models, Gen AI, Agentic AI); 

Ensure the accuracy, completeness, and consistency of customer data within the system by performing regular data cleansing, and validation checks. Ensure proper data entry protocols, duplication control, and timely updates, to support reliable reporting and effective decision-making.

Assist and optimize end-to-end customer service and sales workflows to improve efficiency, responsiveness, and overall customer experience. Assist sales manager to identify gaps and implement best practices, standard operating procedures (SOPs).

Assist and coordinate customer engagement by ensuring timely, accurate, and communication throughout the sales cycle. Support quotation process by standardizing templates, improving turnaround time, and ensuring pricing accuracy in agreement and alignment with customer requirements.

Our Research Scientists serve as the driving force behind our Innovations. We identify and target mechanisms or pathways involved in the disease process, and invent novel therapies to address unmet medical needs. This exceptionally COMPLEX task represents one of the most MULTIDISCIPLINARY endeavours in the field.

INNOVATION also thrives at that intersection of multiple disciplines! In this role as an Associate Director, Imaging and Omics AI Analytics Research, you will have the opportunity to work at that intersection of disciplines to shape innovation in biomarker sciences, influence pipeline decisions, and contribute to a research-driven environment with industry-leading expertise. This role is within our Biomarkers & Data Analytics team at our state-of-the-art research laboratory in Biopolis, Singapore.

If you are PASSIONATE about applying your expertise to address critical unmet needs and accelerate the discovery and development of new therapies, we invite you to join us in pioneering the future of biomarker research for the biopharmaceutical industry.

WHAT YOU CAN EXPECT:

• Opportunity to drive AI-ML/data science innovation at the intersection of multiple disciplines by integrating medical and disease biology, imaging & omics technologies, big data and biobanks.  

• Opportunities for engaging your innovative & creative mind to experiment with new ideas and approaches.

• A supportive working environment that fosters career growth and continuous learning.

WHAT YOU WILL DO :

You will spearhead the research and development of AI/ML algorithms to analyze multimodal medical images (e.g., MRI, CT, OCT), digital pathology and spatial-omics data, as well as molecular biomarkers and other omics datasets, with the goal of discovering and deploying novel biomarker solutions.

You will shape these efforts by collaborating with cross-functional teams to identify key research questions and develop robust AI/ML pipelines for integration into our applications, enhancing biomarker and data analytics solutions for various diseases, including cardiometabolic, immunological, and neurological conditions.

You will partner with internal teams of experts, external research institutions, and technology vendors to identify and access state-of-the-art AI/ML technologies and drive innovation to achieve significant outcomes. One key aspect of your role will be contributing to the development of reusable software/analytics pipelines that serve as foundational AI/ML capabilities, which can be integrated across various applications.

As a result of these initiatives, you will play a crucial role within the team that harnesses big data (such as Biobank, real-world data, and electronic health records) and data science to support both reverse and forward translation. Your efforts will contribute to transforming insights from medical and disease biology into biomarker solutions that enable decision-making in our drug development programs.

In this role, you will present our AI/ML technology and algorithms to a variety of stakeholders, including project teams, senior management, and external partners. You will also author project proposals and technical reports as part of your responsibilities.

Working at the cutting edge of AI/ML technology for pharmaceutical drug discovery and development offers you the opportunity to present and publish your findings, contributing fresh perspectives and diverse viewpoints that can shape the future of the industry.

WHAT YOU MUST HAVE:

You are required to have a PhD in Computer Science, Data Science, Engineering, Physics or a related discipline, along with over 5+ years of experience in applying AI/ML technologies to solve biomedical research questions. Alternatively, a master’s or bachelor’s degree in these areas with 10+ years of relevant experience will also be acceptable.

You are required to have a strong background in machine learning, deep learning, and various advanced neural network architectures (e.g., CNNs, RNNs, GNNs, and Transformers), key learning paradigms (supervised/self-supervised/unsupervised learning, GANs, diffusion modeling etc) and foundation models/LLMs for applications in large-scale medical imaging, omics, and text/EHR data analytics (e.g., for bigdata/biobank applications).

You should possess significant hands-on experience with modern programming languages (e.g., Python, R, Java, JavaScript), ML/DL frameworks (e.g.,  scikit-learn, PyTorch, CUDA, TensorFlow), cloud computing services (e.g., AWS, Azure, Google) and common ML engineering platforms/tools (e.g., MLFlow, Spark, Databricks, Dataiku).

You are required to have understanding of medical imaging modalities (e.g., MRI, CT, PET). It will be an advantage for you to have expertise in image processing techniques (such as image segmentation, registration, and feature extraction) and familiarity with tools like ITK, SimpleITK, OpenCV, or similar frameworks.

It would be ideal for you if you have knowledge in cardiometabolic, immunological, and/or neurological disease biology. However, more importantly, you are expected to demonstrate a strong interest in learning the key concepts in disease biology and in applying that knowledge to drug discovery and development in pharmaceutical R&D.

Your leadership skills in building partnerships and leveraging relationships within and across work groups, along with your ability to engage and persuade others to gain acceptance of ideas & foster commitment, will be critical for unlocking the potential of our talents and investments.

Your proficiency in identifying and understanding problems and opportunities through the analysis of quantitative and qualitative information; choosing the best course of action by establishing clear decision criteria; evaluating alternatives and making timely decisions —will be crucial to your leadership skills required for success in shaping our future.

Finally, your ability in facilitating change by encouraging others to implement better approaches and leading the implementation of change within the workplace; along with creating novel solutions that provide measurable value and experimenting with new ways to address work problems, will be vital for driving innovation and deliver impact.

WHO WE ARE

We are known as Merck & Co., Inc., Rahway, New Jersey, USA in the United States and Canada and MSD everywhere else. For more than a century, we have been inventing for life, bringing forward medicines and vaccines for many of the world's most challenging diseases. Today, our company continues to be at the forefront of research to deliver innovative health solutions and advance the prevention and treatment of diseases that threaten people and animals around the world.

We are a research-driven biopharmaceutical company. Our mission is built on the simple premise that if we “follow the science” and that great medicines can make a significant impact to our world. And we believe that a research-driven enterprise dedicated to world-class science can succeed by inventing medicine and vaccine innovations that make a difference for patients across the globe.

WHAT WE LOOK FOR

Imagine getting up in the morning for a job as important as helping to save and improve lives around the world. Here, you have that opportunity. You can put your empathy, creativity, digital mastery, or scientific genius to work in collaboration with a diverse group of colleagues who pursue and bring hope to countless people who are battling some of the most challenging diseases of our time. Our team is constantly evolving, so if you are among the intellectually curious, join us — and start making your impact today.

We are proud to be a company that embraces the value of bringing diverse, talented, and committed people together. The fastest way to breakthrough innovation is when diverse ideas come together in an inclusive environment. We encourage our colleagues to respectfully challenge one another’s thinking and approach problems collectively. We are an equal opportunity employer, committed to fostering an inclusive and diverse workplace.

About the Company

We are a premier global enterprise solutions and HR technology transformation partner working alongside hyper-scale multinational corporations, complex joint ventures, and global enterprise clusters. By combining advanced master data governance, predictive data modeling, and cutting-edge cloud architecture, we build secure and cohesive digital ecosystems that power intelligent HR operations. We focus on structural data integrity, cross-border data privacy engineering, and cultivating top-tier senior technical advisory talent in Singapore.

About the Job

We are seeking an experienced, elite-level SuccessFactors Data Lead to take complete strategic ownership of the end-to-end data strategy, architecture, and migration delivery across a complex multi-instance global enterprise. In this high-impact position, you will design the data models, master data governance rules, and quality thresholds across multiple SAP SuccessFactors instances, legacy platforms, and fragmented HR tools.

Your mission goes far beyond basic technical ETL (Extract, Transform, Load) execution. You must possess a deep functional command of how HR data behaves inside the SuccessFactors Employee Central engine. You will orchestrate complex multi-cycle data migrations, enforce regional data privacy standards (including GDPR and PDPA), and meticulously build a clean, trusted, and harmonized master data foundation engineered to support advanced human capital analytics and emerging GenAI/agentic frameworks.

Key Responsibilities

HR Data Strategy, Target-State Architecture & Harmonization

• Target-State Modeling: Define and own the enterprise HR data strategy across multiple SuccessFactors instances and legacy platforms, crafting target-state data schemas, position hierarchies, corporate taxonomies, and strict master data standards.

• Global Harmonization: Drive multi-instance data harmonization across global clusters, ensuring complete data consistency across Foundation Objects (business units, cost centers, job frameworks, pay structures), custom fields, and picklist values.

• Multi-Entity Calibration: Design a unified global master data framework that seamlessly accommodates regional legal entity nuances, joint venture structures, and cross-cluster reporting analytics frameworks.

End-to-End Data Migration & Cleansing

• Migration Orchestration: Blueprint, sequence, and execute large-scale data migration cycles (including initial profiling, mock data runs, differential delta mapping, reconciliation, and production cutovers) using specialized tools such as Spinifex, OpenText, or cloud ETL platforms.

• Data Integrity Gates: Formulate comprehensive mapping rules, structural transformation logic, automated validation scripts, and custom Excel data manipulation routines to bridge legacy data stores with SuccessFactors.

• Source-Level Remediation: Design and deploy automated data quality profiling and deduplication frameworks, establishing clear data health KPIs and collaborating with regional business teams to correct anomalies at the source.

• AI Readiness Hardening: Enforce strict data profiling thresholds to guarantee that processed employee records achieve the structural data maturity required for secure GenAI and agentic workflows.

Data Governance, Compliance & Integration Design

• Policy Enforcement: Establish and lead global data governance forums, defining clear data ownership boundaries, data steward accountabilities, centralized data dictionaries, and corporate business glossaries.

• Data Privacy Engineering: Define, configure, and audit strict localized data privacy controls, cross-border data transfer rules, and data masking protocols within SuccessFactors data models to ensure absolute compliance with GDPR and PDPA laws during testing and migration.

• Integration Data Contracts: Partner tightly with the Integration & Reporting Lead to define structural data contracts, API payload definitions, and master data synchronization paths between Employee Central and downstream systems (such as non-SAP HR payroll engines, corporate finance ledgers, and ITSM/ServiceNow configuration databases).

Team Leadership & Value Realization

• Workstream Leadership: Lead, mentor, and coordinate a cross-functional team of data analysts, migration developers, and data stewards across onshore (Singapore) and offshore execution hubs.

• Value Tracking: Establish value tracking metrics to measure data normalization successes, focusing on the reduction of manual reconciliation hours and the optimization of manager self-service data experiences.

Skills & Experience Required

Must-Have Skills (Mandatory for Skills Matching)

• SuccessFactors Data Mastery: Minimum 8+ years of hands-on HR technology experience with expert-level proficiency in HR data architecture, schema mapping, and master data management within the SAP SuccessFactors ecosystem.

• Employee Central Data Model Expertise: Deep functional, hands-on command of the SuccessFactors Employee Central (EC) data structure, including Foundation Objects, Position Management mechanics, and complex employment record schemas.

• Global Migration Lifecycle Execution: Proven experience leading the data track for massive, multi-instance global HR transformation programs, managing automated ETL cycles from legacy landscapes into SuccessFactors.

• Specialized HR Tooling: Practical experience with dedicated HR migration and profiling utilities (e.g., Spinifex, OpenText) or expert-level data manipulation scripting capabilities.

• Data Privacy & Compliance Governance: Demonstrable knowledge of implementing data privacy controls, access masking, and cross-border routing rules in compliance with GDPR and PDPA mandates.

Good-to-Have Skills (Preferred Differentiators)

• Official SAP SuccessFactors certification (Employee Central module preferred).

• Prior experience utilizing enterprise-grade master data management (MDM) platforms or automated data governance consoles.

• Familiarity with integration interface platforms (such as SAP Cloud Integration / CPI middleware) or downstream People Analytics reporting suites (Story Reports).

• Deep comprehension of data maturity indexing required to feed downstream Large Language Models (LLMs) or autonomous agent networks.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Architecture, Information Systems Management, Business Analytics, or a related technical/quantitative discipline.

• Outstanding consultative, workshop facilitation, and stakeholder management skills, with a proven ability to align competing priorities across global corporate divisions.

How to Apply

Please click on the 'apply' button to apply online. For more information, please reach out to Vievien Nathan.

EA License Number: 94C3609

Key Responsibilities

• Build and maintain scalable data pipelines using Python
• Write production-grade Python code specifically for data processing, transformation, and ETL workflows
• Perform data cleaning, preprocessing, and feature preparation for analytics and AI use cases
• Use data analysis and manipulation tools to handle large datasets efficiently
• Develop reusable Python modules for data ingestion and pipeline automation
• Perform exploratory data analysis (EDA) to understand data patterns and quality issues
• Optimize data workflows for performance, scalability, and reliability
• Support data requirements for AI/ML and Generative AI systems
• Build data services and APIs to support downstream AI applications
• Ensure data quality, consistency, and observability across pipelines

Must have skills:

Python & Data Libraries (Hands-on Experience Mandatory)

Candidates must have solid practical experience with:

• Pandas — data manipulation, transformation, and analysis
• NumPy — numerical operations and array-based processing
• Matplotlib — data visualization and reporting
• scikit-learn — basic ML workflows and model evaluation
• PyTorch — deep learning and AI model experimentation

AI / Generative AI Enablement

• Prepare and structure datasets for ML and LLM-based systems
• Support integration of AI models into data pipelines and applications
• Enable workflows for Generative AI use cases (RAG systems, agent workflows)
• Work with multiple AI model providers:
• OpenAI
• Anthropic
• LLaMA
• Mistral
• Exposure to AI orchestration frameworks such as LangChain, AutoGen, and CrewAI

Core Requirements

• Solid hands-on Python coding expertise focused on data systems (critical requirement)
• Ability to write clean, efficient, production-grade Python code
• Thorough understanding of data structures, ETL pipelines, and data workflows
• Experience working with large-scale structured and unstructured data
• Solid SQL skills for data extraction and manipulation
• Understanding of data modeling and analytics workflows
• Ability to support end-to-end data-to-AI pipelines

Good to Have

• Experience with big data or distributed processing systems
• Understanding of vector databases and embedding-based retrieval systems
• Experience building APIs or services for data/AI systems
• Familiarity with cloud platforms (AWS, Azure, GCP)
• Exposure to production monitoring and data observability tools

Role Overview

We are looking for an experienced Senior Data Engineer to build scalable, secure, and high-performing data solutions that support digital transformation and data-driven decision-making. In this role, you will design and maintain data pipelines, data models, and data warehouse solutions while working closely with business users, IT teams, and data stakeholders across complex technology environments.

Job Responsibilities

• Translate business data requirements into technical specifications.
• Collaborate with IT teams on technology stack, infrastructure, and security alignment.
• Design and build data ingestion pipelines to collect, clean, merge, and harmonize data from multiple source systems.
• Monitor databases and ETL systems, including capacity planning, maintenance, performance tuning, and issue prevention.
• Construct, test, and maintain reusable data models based on end-user requirements.
• Design and build secure mechanisms for users and systems to access data from the data warehouse.
• Research, propose, and develop new technologies and processes to improve data infrastructure.
• Work with data stewards to establish and enforce data governance policies, best practices, and procedures.
• Maintain data catalogue, metadata, and data lineage documentation.
• Implement data quality checks and validation processes to ensure data accuracy and consistency.
• Implement data security best practices, including access control, encryption, and data masking.

Job Requirements

• Bachelor’s Degree in Computer Science, Software Engineering, Information Technology, or related disciplines.
• Strong understanding of system design, data structures and algorithms, data modelling, data access, and data storage.
• Hands-on experience with cloud technologies such as AWS, Azure, or Google Cloud.
• Experience with Databricks.
• Experience in designing, building, and maintaining batch and real-time data pipelines.
• Experience with orchestration frameworks such as Airflow or Azure Data Factory.
• Proficient in Python, Shell Scripting, and SQL.

Preferred Requirements

• Familiarity with CI/CD pipelines.
• Familiarity with DevOps tools such as Docker, Git, and Terraform.
• Experience implementing technical processes for data security, data quality, and data governance.
• Familiarity with government systems and policies relating to data governance, data management, data infrastructure, and data security will be an advantage.
• Experience in Climate and Weather domains will be an added advantage.

Responsibilities

• Perform duty to manage data centre (DC) operations, maintenance, troubleshooting, project rollout and facilities related matters.
• Perform DC monitoring and maintenance on infrastructure systems, critical facilities and associated equipment.
• Perform preventive and corrective support to scheduled or unscheduled maintenance on DC infrastructure systems, critical facilities equipment and/or services.
• Ensure all subcontractors deliver a quality and competent service and all contractual obligations are met. Supervise the vendors to all scheduled and adhoc activities related to DC facilities.
• Perform DC and critical facilities work on environmental and management programs
• Perform equipment functionality test and data analysis
• Perform assets management duty, including maintaining of inventory, change and control programs and purchase of parts and supplies
• Promptly respond and attend to incident and/or emergency situations
• Provide standby support upon activation for shift duty stand-in and/or other coverage
• Conduct routine, sanity check and ongoing assessment of DC infrastructure systems and critical facilities operations

Requirements:

• Nitec / Higher Nitec / Diploma in Electrical/Mechanical/DC Infrastructure or relevant engineering discipline (Electrical, Mechanical or related fields)
• Additional certifications relevant to the industry is an added advantage
• 1 -2 years experience maintaining electrical, mechanical, fire protection system in facility management, particularly handling critical systems would be an added plus
• Strong problem-solving abilities, communication skills, and the ability to work independently and as part of a team
• Proficient in Computer skills eg. microsoft office, google emails, docs etc

5+ years of experience in data migration, data conversion, data quality, or data management projects.

• Experience supporting migration from legacy systems to modern enterprise applications, data platforms, or cloud-based solutions.

• Strong understanding of data profiling, source-to-target mapping, data cleansing, data transformation, reconciliation, and validation.

• Experience working with relational databases such as Microsoft SQL Server, PostgreSQL, Oracle, MySQL, or equivalent.

• Familiarity with ETL, ELT, or data processing tools such as Python, SSIS, Informatica, Talend, AWS Glue, or equivalent.

• Ability to work with technical teams to validate migration logic, transformation rules, migration jobs, and exception reports.

• Experience preparing clear migration documentation, data mapping specifications, cutover plans, validation reports, and reconciliation summaries.

• Strong analytical, problem-solving, and stakeholder management skills.

• Ability to communicate data issues clearly to both technical and non-technical stakeholders.

• Experience working in large-scale, secure, regulated, or public sector environments is advantageous.

Job Description:

• Responsible for the end-to-end ownership of Murex MX.3 Datamart reporting design, architecture, configuration, and delivery within a corporate banking transformation programme in Singapore.
• The role encompasses requirements analysis, datamart data model design, Datamart object configuration (dynamic tables, feeders, processing scripts, scanner templates), report development across Front Office, Back Office, Market Risk, Credit Risk, and Finance streams, and the strategic optimisation of batch report performance and EOD processing workflows.
• The incumbent will act as the primary Datamart workstream lead and Subject Matter Expert (SME), responsible for both hands-on technical delivery and the leadership of a team of Datamart reporting consultants and developers.
• The role requires deep expertise in MX.3 Datamart architecture, the Murex reporting engine, SQL optimisation, and capital markets reporting domains, combined with the team management and stakeholder engagement capabilities expected at a senior Lead level within a Tier 1 bank transformation programme.

Reporting Requirements & Architecture Design:

• Own and lead the Datamart reporting workstream for the MX.3 transformation programme, covering all user streams: Front Office (PnL, positions, trading blotters), Back Office (settlements, confirmations, nostro), Market Risk (VaR, stress testing, sensitivities), Credit Risk (PFE, CVA, CCR), and Finance (accruals, mark-to-market, P&L attribution).
• Engage directly with business stakeholders — including traders, risk managers, finance controllers, and operations heads — to gather, analyse, and formalise reporting requirements into detailed Business Requirement Specifications (BRS) and Technical Design Documents (TDDs).
• Understand the Murex system setup at the client: the organisation of support teams, EOD procedures, report delivery processes, and the interdependencies between Datamart and other MX.3 modules (FO, BO, Risk, Finance, Integration).
• Design a generic Datamart data model aligned to the bank's reporting taxonomy, then create the required Datamart objects (dynamic tables, feeders, extractions, scanner templates, processing scripts) to support all reporting use cases.
• Segregate and categorise reports by users, products, creation classes, fields required, complexity, and execution frequency to build a scalable and maintainable reporting catalogue.
• Communicate regularly with business Team Leads and programme stakeholders to ensure all Datamart deliverables are progressing as planned and expectations are actively managed.

Datamart Configuration, Development & Optimisation:

• Perform in-depth analysis of the Datamart setup and table structures to identify redundant objects, minimise batch execution time, and maximise reuse of existing Datamart components.
• Develop and configure all Murex Datamart objects: dynamic tables (PL, CS, DT, MV, LRB, PLVAR), feeders, batch of feeders, processing scripts, scanner templates, extractions, reporting tables, and pre/post filter conditions.
• Design and implement Simulation-based Reports and Risk Matrix-based reports for market risk and credit risk reporting consumers within the MX.3 platform.
• Configure and optimise EOD batch execution: implement parallel feeding strategies, resolve batch bottlenecks, tune query performance, and manage processing script sequencing within Control-M or equivalent job schedulers.
• Implement dataset historisation techniques within the Datamart to support time-series reporting, regulatory lookback requirements, and management information (MI) aggregation.
• Develop and maintain stored procedures, extractions, and complex SQL logic (Sybase/Oracle) for data processing, report population, and cross-module data joins leveraging the Murex FIN schema.
• Develop simulation views and scenario analysis reporting objects to support pre-trade and risk management reporting requirements for Front Office and Risk users.

Report Validation, Reconciliation & Quality Assurance:

• Execute processing scripts and batch jobs manually or via scheduling tools (Control-M), and reconcile Datamart report extraction output against onscreen MX.3 views and Mreport output to validate data accuracy.
• Analyse and resolve discrepancies arising from filter condition changes, feeder configuration differences, or data model modifications between Datamart report runs.
• Define and execute Datamart-specific test cases for SIT and UAT; ensure all test documentation and deliverables are consistent with programme testing standards and acceptance criteria.
• Assist in effort estimation for Datamart development and UAT scope; maintain accurate delivery tracking and escalate issues or risks to the Programme Manager in a timely manner.
• Participate in structured peer reviews of requirements, technical specifications, and testing documentation; provide constructive feedback and maintain quality standards across the Datamart workstream.

Migration, Integration & Market Data:

• Lead the migration of legacy Mreport-based reports to MX.3 Datamart equivalents, including gap analysis, mapping documentation, configuration build, and parallel run reconciliation.
• Manage market data integration and validation within the Datamart, ensuring rate curves, volatility surfaces, FX rates, and credit spread data are correctly sourced and represented in Datamart report calculations.
• Leverage NeoXam Data Hub scripting or equivalent data hub capabilities for data pipeline integration between MX.3 Datamart and downstream BI, regulatory reporting, or finance consolidation platforms.
• Coordinate with the Integration Lead to align Datamart extraction design with the broader enterprise data flow architecture, ensuring consistency of data lineage from trade booking through to report output.
• Configure MDCS (Market Data Curve Server), mxres configuration files, and launcher flags to support Datamart batch execution and reporting server performance requirements.

Team Leadership & General Management:

• Lead, manage, and mentor a team of Datamart reporting consultants and developers; delegate work effectively, review team output, and maintain delivery quality across all Datamart stream deliverables.
• Responsible for end-to-end ownership of Datamart reporting deliverables: from requirements intake through design, development, testing, UAT support, and post-deployment production validation.
• Ensure all team members are guided on best practices for Datamart configuration, object reuse strategies, batch optimisation, and coding standards within the MX.3 reporting framework.
• Demonstrate the ability to work proactively and independently where required, displaying strong initiative in identifying reporting gaps, performance issues, or data quality risks before they impact programme delivery.
• Contribute to programme governance forums by providing Datamart workstream status updates, risk and issue logs, and delivery milestone tracking to the Programme Manager and Steering Committee.

Requirements:

• 10+ years of hands-on experience as a Murex Datamart Developer, Consultant, or Reporting Lead on MX.3 programmes within corporate or investment banking environments.
• Mandatory in-depth expertise in MX.3 Datamart architecture and configuration: Datamart management, dynamic tables (PL, CS, DT, MV, LRB, PLVAR), feeders, batch of feeders, processing scripts, scanner templates, extractions, and reporting tables.
• Thorough understanding of MX reporting architecture, the MX.3 data model, the Murex FIN schema, and MXRes configuration files and launcher flags as they relate to Datamart reporting execution.
• Strong experience in Market Risk and Credit Risk report development within MX.3 Datamart, including Simulation-based Reports, Risk Matrix reports, VaR attribution, sensitivities, and PFE reporting.
• Proven experience with Mreport framework and Mreport to Datamart migration projects — including gap analysis, mapping, and parallel reconciliation — is highly desirable.
• Demonstrated track record of leading a Datamart reporting workstream or team across at least two full SDLC cycles within a capital markets platform implementation or upgrade programme.
• Good understanding of capital markets products and trade lifecycle across: FX (mandatory), Money Markets, Interest Rate Derivatives, Fixed Income, Equity Derivatives, and Credit Derivatives.
• Experience in NeoXam Data Hub scripting or equivalent data integration platforms for connecting MX.3 Datamart outputs to downstream systems is advantageous.
• Proven ability to gather, document, and validate complex reporting requirements from diverse business stakeholders (traders, risk managers, finance controllers, operations).

Education;

• Bachelor's degree or higher in Finance, Computer Science, Information Technology, Financial Engineering, or a related discipline.
• Formal Murex training or certification in Datamart and Reporting modules is advantageous. Master's degree in a quantitative or technical field is a plus.

Technical Skills:

• Excellent SQL programming skills (Sybase and Oracle); proficiency in PL/SQL for stored procedures, complex joins, and performance-optimised query design across the Murex FIN schema.
• Unix / Linux experience is necessary; Shell scripting (awk, sed, Perl, Bash) is highly desirable for batch automation, data processing, and monitoring script development.
• Python scripting for data processing, reconciliation automation, and Datamart batch management; experience with Python in NeoXam Data Hub or similar environments is advantageous.
• Experience with at least one reporting / BI tool: Actuate eRD Pro (preferred), Crystal Reports, MicroStrategy, or equivalent; Excel VBA for report automation and data validation is a plus.
• Familiarity with scheduling tools: Control-M (preferred), AutoSys, or equivalent for Datamart batch job management, dependency configuration, and execution monitoring.
• Desirable: knowledge of MRA/MRE or MLC module configuration; familiarity with Murex Pricing, Trade Repository, Trade Validation, MDCS, and MxML Exchange workflows.
• Java knowledge (especially Apache Camel, Maven) for integration touchpoints between Datamart and downstream systems is an advantage.

As a Data Scientist at Micron, you will employ techniques and theories drawn from areas of mathematics, statistics, semiconductor physics, materials science, and information technology to uncover patterns in data from which predictive models, actionable insights, and solutions can be developed.

You will interact with experienced Data Scientists, Data Engineers, Business Areas Engineers, and UX teams to identify questions and issues for data analysis projects and improvement of existing tools. In this position, you will help develop software programs, algorithms and/or automated processes to cleanse, integrate, and evaluate large datasets from multiple disparate sources. There will be significant opportunities to perform exploratory and new solution development activities.

In This Role You Will Have The Following Responsibilities

• Strong desire to grow a career as a Data Scientist in highly automated industrial manufacturing doing analysis and machine learning on terabytes and petabytes of diverse datasets and to deliver meaningful end-to-end solutions for users.

• Experience in the areas: computer vision, statistical modeling, deep learning, generative AI, feature extraction and analysis, supervised/unsupervised/semi-supervised learning. Exposure to the semiconductor industry is a plus but not a requirement.

• Design and deploy computer vision models for object detection, image segmentation and anomaly detection.

• Stay abreast of the latest research and advancements in machine learning and computer vision and apply them to real-world problems.

• Ability to extract data from different databases via SQL and other query languages and applying data cleansing, outlier identification, and missing data techniques.

• Coordinate production deployment activities, including cross-functional communications, approval and execution of changes in live environments.

• Strong verbal and written communication skills.

Required Qualifications and Technical Experience

• Mater/PHD Degree in Operation Research, Industry Engineering, Statistics with a strong academic foundation in linear programming and optimization

• Minimum 3 years of experience in operation research/optimization, preferably has working experience in the semiconductor industry and have applied optimization techniques in their daily work

• Strong foundation in Linear programming optimization modeling, advanced analytics, and  machine learning techniques.

• Ability to extract data from multiple databases using SQL and other query languages, including experience with data cleansing, outlier detection, and handling missing data.

• Strong proficiency in Python and linear programming, SQL, C#

• Proficiency in data visualization tools such as Tableau, Power BI, and related techniques.

• Proficiency in web development technologies, including Angular, FastAPI, and Docker.

Responsibilities

• Develop and maintain ETL/ELT pipelines using Python, PySpark, and SQL.
• Build and support batch and real-time data processing solutions.
• Integrate data from multiple sources and ensure data quality and reliability.
• Monitor, troubleshoot, and optimize data pipelines and workflows.
• Collaborate with business, analytics, and technology teams to deliver data-driven solutions.
• Support cloud-based data platforms and data warehousing initiatives.
• Develop automation and monitoring solutions to improve operational efficiency.
• Any other ad-hoc duties as assigned by supervisor.

Requirements

• Bachelor's Degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline.
• 3+ years of Data Engineering or ETL development experience.
• Strong proficiency in Python, PySpark, and SQL.
• Experience with Hadoop, Spark, Kafka, or similar big data technologies.
• Knowledge of data warehousing and data modeling concepts.
• Experience with cloud platforms such as Azure Data Factory, Azure Synapse, Databricks, or Azure Data Lake.
• Strong problem-solving and stakeholder management skills.

Technical Skills

• Experience with Apache Flink or real-time streaming technologies.
• Exposure to Power BI, Tableau, Qlik, or other BI tools.
• Familiarity with AI/LLM frameworks such as LangChain, LangGraph, or RAG solutions.
• Experience within banking, financial services, or large enterprise environments.
• Tech Stack: Python, PySpark, SQL, Hadoop, Spark, Kafka, Azure, Databricks, Power BI/Tableau.

Interested applicants, please email your resume to Andre Chua Jing Ming

Email: andrechua@recruitexpress.com.sg

CEI Reg No: R1989053

EA Licence No: 99C4599

Recruit Express Pte Ltd

Responsibilities

• Develop and maintain ETL/ELT pipelines using Python, PySpark, and SQL.
• Build and support batch and real-time data processing solutions.
• Integrate data from multiple sources and ensure data quality and reliability.
• Monitor, troubleshoot, and optimize data pipelines and workflows.
• Collaborate with business, analytics, and technology teams to deliver data-driven solutions.
• Support cloud-based data platforms and data warehousing initiatives.
• Develop automation and monitoring solutions to improve operational efficiency.
• Any other ad-hoc duties as assigned by supervisor.

Requirements

• Bachelor's Degree in Computer Science, Information Technology, Engineering, Data Science, or a related discipline.
• 3+ years of Data Engineering or ETL development experience.
• Strong proficiency in Python, PySpark, and SQL.
• Experience with Hadoop, Spark, Kafka, or similar big data technologies.
• Knowledge of data warehousing and data modeling concepts.
• Experience with cloud platforms such as Azure Data Factory, Azure Synapse, Databricks, or Azure Data Lake.
• Strong problem-solving and stakeholder management skills.

Technical Skills

• Experience with Apache Flink or real-time streaming technologies.
• Exposure to Power BI, Tableau, Qlik, or other BI tools.
• Familiarity with AI/LLM frameworks such as LangChain, LangGraph, or RAG solutions.
• Experience within banking, financial services, or large enterprise environments.
• Tech Stack: Python, PySpark, SQL, Hadoop, Spark, Kafka, Azure, Databricks, Power BI/Tableau.

Interested applicants, please email your resume to Andre Chua Jing Ming

Email: andrechua@recruitexpress.com.sg

CEI Reg No: R1989053

EA Licence No: 99C4599

Recruit Express Pte Ltd

Contributes to the development of new analytics tool, software, and approaches, including the design, development, troubleshooting and debugging.

  *   Ongoing maintenance, update and support of the existing programming and analytic tools

  *   Develop, implement and maintain server and database infrastructure, hardware and software to ensure maximum tool uptime and performance.

  *   Execute end-to-end data processing workflows, ensuring data is accurately ingested, cleaned and structured across corporate systems.

  *   Manage and monitor data flows between current and future infrastructure components to maintain data integrity and consistency.

  *   Analyze processed data to uncover trends, patterns and operational performance metrics using statistical techniques.

  *   Exercises significant independent judgment to determine best method for accomplishing work and achieving objectives

  *   Leads and /or provides expertise to functional project teams and may participate in cross-functional initiatives.

The requirements:

  *   5 years of hands-on experience in data engineering and analytics

  *   Strong skills in statistical tools and programming languages such as Python, R, etc.

  *   Experience with data analysis / visualization tools and software like Power BI, Looker, Databricks etc.

  *   Proficiency in SQL for data extraction and manipulation.

  *   Attention to detail and a commitment to data accuracy.

  *   Proactive approach to identifying issues and providing solutions.

  *   Strong analytical and problem-solving skills. Ability to analyze complex datasets and translate data into actionable insights.

  *   Ability to present complex information in an understandable and compelling manner.

  *   Excellent written and verbal communication skills

  *   Ability to work independently and collaboratively as part of team

•You will be responsible for end-to-end delivery of enterprise data and analytics solutions leveraging traditional and modern Data architecture. Experience with Financial Crime Analytics, Finance & Credit Risk Analytics, Credit Scoring & Decision systems, Retail & Wholesale Datamarts will of advantage

•The role spans requirements analysis, solution design, testing, implementation, and production support ensuring high-quality, scalable, and compliant data platforms that support advanced analytics and AI initiatives.

Key Responsibilities

•Lead end-to-end solution delivery for data and analytics across the full SDLC.

•Analyze business and regulatory requirements, translate them into scalable solution designs & provide estimations.

•Communicate complex technical and architectural concepts to business and senior stakeholders in a clear, simplified manner.

•Review and approve test strategies, functional test cases, and data validation approaches.

•Manage risks and issues related to scope, data quality, regulatory commitments, and delivery timelines.

•Participate in product and platform evaluations (RFPs, PoCs) for data, analytics, and AI tooling.

•Partner with production support team to conduct root cause analysis, resolution, and preventive controls.

•Lead innovation and modernization initiatives, including data discovery, cataloguing, governance, and AI enablement.

•Drive productivity, efficiency & quality improvements across delivery and operational processes.

•Ability to design data architectures supporting NLP and AI-driven analytics.

FUNCTIONAL SKILLSETS

Analytics Domains

•Financial Crime Analytics Transaction Monitoring, Customer Due Diligence, Sanctions & Payments Screening

•Finance & Credit Risk Analytics Financial reconciliation, Allocation, Performance management, Regulatory and Management reporting, Credit risk exposure, NPL, Counterparty risk, Basel & IFRS9 input variables

Enterprise Data, Analytics & Unstructured Data Enablement

•Proven experience delivering large-scale analytics platforms within financial services spanning structured, semi-structured, and unstructured data

•Strong capability in requirements analysis and functional design for analytics use cases involving Transactional data, Investigator narratives, Case notes and alerts, Policy & Customer communications documents

•Experience defining data quality, governance, lineage, and reconciliation controls for both structured and NLP-derived datasets.

Unstructured Data & NLP-Enabled Analytics

•Ability to define data architectures and data flows that ingest, curate, and govern unstructured and semi-structured data within enterprise data platforms.

•Experience translating business requirements into NLP-enabled analytical use cases, such as Text classification and categorization, Entity & relationship extraction, Risk indicator identification, Summarization of alerts, cases, or documents

Knowledge Graph & Relationship Based Analytics

•Ability to design and govern an enterprise knowledge layer defining relationship taxonomies, entity resolution rules, and linkage logic

•Ability to translate use cases into relationship driven analytical designs, such as Network based risk identification, Hidden association and indirect exposure analysis, Related party and concentric risk detection

Requirements

Data Platforms & Architecture

•Open table formats: Apache Iceberg, Delta Lake, Apache Hudi

•Distributed processing & query engines: Spark, Trino/Presto, Hive

•Cost optimization strategies: tiered storage, lifecycle management, workload governance

Programming & Analytics

•SQL, BTEQ, GCFR

•Python (Pandas, NumPy)

•BI & visualization tools: Power BI, QlikSense

Data Integration & Quality

•Informatica suite: PowerCenter, BDM, IDQ, Enterprise Data Catalogue

•Data ingestion patterns: batch, CDC, streaming

•Data validation, quality controls, and reconciliation frameworks within environments

Governance, Risk & Compliance

•Data modelling, critical data elements, regulatory reporting

•Fine-grained data access controls (row-level, column-level, masking)

•Metadata management, lineage, and impact analysis

•Compliance with BCBS 239, MAS, AML/CFT, and internal data standards

Big Data Platforms

•Cloudera Hadoop distribution: Hive, Impala, Spark, Iceberg, Trino

Data engineer (Azure) – Synapse and Pyspark, Python, Datawarehouse and Azure Data Explorer, Azure Devops

Job Scope

• Design, review and development of Pyspark scripts. Testing, troubleshooting of data pipelines, orchestration.

• Designing and developing reports and dashboards in PowerBI,setting up access control with row level security DAX query experience.

• Establishing connections to source data systems such as on-prem databases, IOT devices, APIs.

• Managing the collected data in appropriate storage/data-base solutions e.g. file systems, SQL servers, Big Data platforms such as Hadoop, HANA, etc. as required by the specific project requirements.

• Design, development of relevant data pipelines using pyspark, copy data activities for batch ingestion.

• Performing data integration e.g. using database table joins, or other mechanisms at an appropriate level as required by the analysis requirements of the project.

• Deployment of pipeline artifacts from one environment to the other using Azure Devops.

Skills & Experience

• Bachelor’s Degree in Computer Science or Engineering with 2 years of experience in Azure Data engineering, Python, Pyspark or Big Data development.

• Sound Knowledge of Azure Synapse analytics for pipelines, orchestration, set up.

• 1-2 experience in Visualization design and development with Power BI. Knowledge on row-level security, access control.

• Sound experience in SQL, Datawarehouse, data marts, data ingestion with Pyspark and Python.

• Expertise in developing and maintaining ETL processing pipelines in cloud-based platforms such as AWS, Azure, etc. (Azure Synapse or data factory preferred)

• Team player with good interpersonal, communication, and problem-solving skills.

• Preferred to have Devops expertise.

Candidates without prior experience are welcome to apply as on the job training would be provided.

Working hours :

8:30am to 6pm (Monday to Friday) onsite, no hybrid option.