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.

Purpose of the role – mission: The Data Scientist role is responsible for designing and managing universe studies, setting up the extrapolation for Retail Panels, documenting methodologies, ensuring quality assurance, and monitoring key performance indicators (KPIs) related to Panel Health. This role requires a strong background in data analysis, statistical modeling, and quality control processes as well as strong production system processes for PoS. This role supports the China market.  

Key activities:  

• Methodology and Universe Studies: Design and manage universe studies, including project management.  

• Document methodologies for transparency and provide clear explanations of existing methods.  

• Review results of universe studies and insert changes in the POS Manager.  

• Conduct impact analysis of universe studies.  

• Design and simulate extrapolation setups for new panels and sign off on the designs.  

• Quality Assurance: Optimize samples by analyzing shop contributions, detecting MDQC (Market Data Quality Check) outliers, meeting target sample requirements, and addressing issues like empty shops and slow sales.  

• Detect and address systematic methodological issues and prepare cleanup impacts for critical findings (end-to-end).  

• Modeling and Extrapolation: Model missing retailers completely outside the system and maintain complex models.  

• Support the setup of modeling missing retailers in the system and hand over to Stat Ops for ongoing maintenance and execution.  

• Implement new country-channel setups, including reviewing channel definitions, designing universes and samples, and providing setup instructions.  

• Quality Monitoring: Resolve Level 2 methodology clarification issues.  

• Monitor KPIs and conduct root cause analysis (RCA) for panel health, focusing on samples, missing retailers, universes, copy shops, and MDQC related to samples and extrapolation.  

• Define and specify improvement points for panel health.  

The Data Operations Analyst  is responsible of reformatting the retailer and vendor input files, validations, outlier checks and sending the deliverables to the next workstream in a correct and timely manner.  

• Be the contact for questionable sales and stores trend, leading the resolution in a client-focused and timely manner in cooperation with Input Validation, Retailer Vertical/ Retailer Engagement team and other downstream functions. To be able to identify, investigate and coordinate the resolution of data, process, or product related queries 
• Plan and execute complex daily personal workload and support to meet departmental and company schedules 
• Analyze and identify gaps and areas for improvement in reformatting and validations environment (CIP – Consumer Information platform) and drive convergence of processes and tools 

• Providing accurate and timely feedback to respective country teams, driving SOP and use of best-demonstrated practices 
• Working across relevant Operations/Enablement teams to ensure delivery to client expectations and satisfaction 
• Operate in a virtual/multi-cultural environment, liaising with stakeholders and colleagues

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.

• Manage Lockout/Tagout (LOTO) procedures and ensure compliance across all contractors.
• Act as the primary liaison between construction, commissioning, and operations teams regarding energy safety.
• Review and approve energy isolation plans and permits.
• Conduct field inspections and audits to ensure adherence to safety protocols.
• Stop unsafe work practices and enforce OSHA and NFPA 70E standards.
• Monitor and report on energy usage and performance metrics.
• Validate mechanical and electrical system performance during commissioning.
• Assist in implementing energy-saving strategies and sustainability best practices.
• Maintain detailed records of energy control activities and compliance metrics.
• Train and mentor teams on electrical safety and energy isolation procedures.

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.

• Data-centre Typology: To front projects and provide technical leadership and governance, supporting work winning, design, and multi-disciplinary delivery for Singapore markets
• Develop architectural concepts, designs, feasibility studies that meet client requirements
• Act as the key point of accountability, aligning client requirements with technical execution and team performance
• Managing budgets and risks, and ensuring high-quality delivery while balancing client and internal needs

If the role resonates with you and your professional experience complements the responsibilities listed, send your resume to koh.dickson@bayesrecruitment.com

Dickson Koh, EA Registration R1103367

www.bayesrecruitment.com

Job Description

• Design and implement ETL/ELT pipelines and data workflows
• Manage and maintain scalable data warehousing solutions
• Ensure data quality, consistency, and integrity across sources

Requirements

• 0 to 1 Year Experience in Data Engineering
• Polytechnic Diploma or Degree in Computer science/Data Science is essential
• Freshers with strong SQL and Python scripting will be considered
• Willing to learn new technologies and undergo rigorous training
• strong communication skills and ability to work in a team is essential

Data Center Sourcing Manager

Job Summary

Altuscloud is seeking a Data Center Sourcing Manager to support the sourcing and procurement of colocation capacity for our cloud infrastructure platform. This role will be responsible for identifying suitable data center partners, conducting technical and commercial evaluations, and supporting vendor selection and contract negotiations to secure reliable and cost-effective infrastructure capacity.

The successful candidate will work closely with Engineering, Infrastructure, and Commercial teams to support the Company's regional growth and expansion plans.

Key Responsibilities

Data Center Sourcing & Procurement

• Support the development and execution of data center sourcing strategies to meet business growth requirements.
• Identify, evaluate, and engage potential colocation providers and infrastructure partners.
• Conduct technical and commercial assessments of data center facilities and service offerings.
• Support capacity planning activities and assist in securing suitable colocation space, power, and connectivity resources.
• Maintain relationships with existing and prospective data center providers.

Technical Evaluation

• Perform technical due diligence on data center facilities, including:Power availability and redundancyCooling systems (air-cooled and liquid-cooled environments)Network connectivity and carrier ecosystemSecurity, operational processes, and facility resilience
• Work with internal technical teams to validate infrastructure requirements and deployment feasibility.
• Assist in evaluating solutions for high-density compute environments.

Vendor Management & Commercial Support

• Prepare and manage Requests for Proposal (RFPs), Requests for Quotation (RFQs), and vendor evaluation processes.
• Support commercial discussions and contract negotiations with data center operators and service providers.
• Review pricing structures, service level agreements (SLAs), and commercial terms.
• Coordinate internal approvals and maintain procurement documentation.

Market Research & Industry Analysis

• Monitor market developments, pricing trends, and capacity availability across key regions.
• Conduct competitive and market analysis to support sourcing decisions.
• Provide insights and recommendations on emerging data center technologies and infrastructure trends.

Cross-Functional Collaboration

• Collaborate with Engineering, Infrastructure, Operations, Finance, Legal, and Business teams throughout the sourcing lifecycle.
• Support contract review and vendor onboarding processes.
• Participate in internal planning and reporting activities related to infrastructure expansion projects.

Requirements

• Bachelor's Degree in Engineering, Supply Chain Management, Business Administration, Information Technology, or a related discipline.
• At least 4 years of relevant experience in data center sourcing, colocation procurement, infrastructure procurement, vendor management, or related fields.
• Experience evaluating or procuring data center capacity, including colocation space, power, cooling, and connectivity services.
• Good understanding of data center infrastructure concepts, including power density, cooling technologies, redundancy models, and networking fundamentals.
• Strong communication, stakeholder management, and negotiation skills.
• Ability to work effectively with both technical and commercial teams.
• Strong organizational and project coordination capabilities.
• Willingness to undertake occasional regional travel when required.

Preferred Qualifications

• Experience supporting cloud infrastructure, AI infrastructure, high-performance computing (HPC), or related technology environments.
• Exposure to data center providers and infrastructure markets in Singapore, APAC, or other international regions.
• Familiarity with high-density rack deployments and advanced cooling technologies.
• Experience working in a fast-growing technology, cloud, or infrastructure-related business environment.

Equal Opportunity Statement

Altuscloud is an equal opportunity employer. We are committed to creating an inclusive and diverse workplace and welcome applications from qualified candidates regardless of background.