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.

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.

• 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.

Responsibilities:

• Data Infrastructure: Build, implement, and maintain scalable data pipelines and storage architectures.
• Data Quality: Maintain strong data integrity by ensuring reliability, consistency, and accuracy across all data processes.
• Performance Optimization: Enhance system efficiency by tuning data processing workflows and improving large-scale performance.
• Process Improvement & Mentoring: Strengthen data engineering practices while providing guidance and support to junior engineers.
• Cross-Functional Collaboration: Partner with business analysts, data scientists, and backend teams to deliver timely and actionable data solutions.

Qualifications:

• 5+ years’ experience in data engineering or backend roles, with strong programming skills in Python or Java/Scala.
• Hands-on experience with big data tools: Spark, Flink, Kafka, Airflow, and cloud platforms (AWS, GCP, Azure); proficient in SQL.
• Skilled in designing and maintaining data models, warehouses, and ETL/ELT pipelines for scalable, reliable systems.
• Knowledgeable in data quality, governance, security, and compliance best practices.

We regret only shortlisted candidates will be contacted. All applications will be handled confidentially. By submitting your application, you agree to the collection, use, retention, and disclosure of your personal information to prospective employers.

Wecruit Pte Ltd
EA License No: 20C0270
EA Personnel: Nyon Hock Sen (Aden)
EA Personnel Reg No: R24124070

·      Administer and manage Redis clusters for low-latency caching and real-time transaction processing.

·      Manage MongoDB clusters (replication, sharding) for scalable transaction and semi-structured data storage.

·      Working knowledge of Hadoop ecosystem (Hadoop, Hive, Pig, Oozie, Hbase, Flume, sqoop) using both automated tool sets as well as manual processes.

·      Support and maintain Hadoop (HDP)clusters for batch processing, analytics, and regulatory reporting.

·      Perform cluster lifecycle management provisioning, scaling, patching, and decommissioning nodes.

·      Ensure 24x7 availability and resilience of production systems supporting payment flows.

·      Manage and optimize Apache Kafka for high-throughput, real-time payment event streaming.

·      Support Apache NiFi for ingestionpipelines from upstream payment systems and external partners.

·      Work with AWS EMR for scalableprocessing of transaction data and reconciliation workloads.

·      Administer HDFS, ensuring optimal replication,storage utilization, and fault tolerance.

·      Manage OpenSearch / Elasticsearchclusters for transaction search, audit trails, and operational dashboards.

Required Skills & Experience

·      6–8 years of experience in Big Data / DataPlatform Engineering in enterprise environments.

·      Strong hands-on experience with:

·      Hadoop ecosystem (HDFS, YARN, MapReduce, HDP)

·      Apache Kafka (high-throughput environments)

·      Redis and MongoDB clusters

·      OpenSearch / Elasticsearch

·      Apache NiFi

·      AWS EMR + good knowledge of AWS Cloud.

·      Strong expertise in Linux system administration and scripting (Shell/Python)

·      Experience with Kerberos, data security, and access governance

·      Proven experience in handling high-volume, low-latency systems (preferably payments/trading) 

EA License No: 11C4879 / Registration ID : R1218583

Apar Technologies Pte Ltd, Singapore

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