131 Data Engineering jobs in Singapore

We are an IT MES (Manufacturing Execution System) team based in Woodlands, supporting Seagate's global factory operations in Singapore, Malaysia, US, Thailand, and China. Our core mission is to design and implement scalable data integration solutions that power MES and Factory IT applications.

Our focus includes Database ETL processes, complex SQL development, and Python-based automation to optimize data flows and ensure system reliability. Beyond traditional data engineering, we are also exploring Generative AI and Agentic AI solutions to modernize data platforms and create new value for factory operations.

This internship is ideal for students who are passionate about ETL/Data Engineering with Oracle, eager to sharpen their Python skills, and curious about the application of LLMs and AI frameworks in enterprise IT.

As a Data Engineering Intern, you will:

• Work with senior engineers on ETL processes in Postgres / Oracle, including writing and optimizing stored procedures, functions, and packages.
• Develop and optimize complex SQL queries to support data extraction, transformation, and reporting needs.
• Use Python for automation, data processing, and proof-of-concepts.
• Collaborate with Application Architects and Business SMEs to deliver data integration solutions supporting MES and factory applications.
• Contribute to projects involving LLMs, LangChain, LangGraph, and Marimo notebooks for GenAI-enabled data pipelines.
• Support testing, troubleshooting, and documentation to ensure system reliability and performance.

• Strong foundation in SQL and relational database concepts.
• Hands-on skills in Database stored procedures, triggers, and performance tuning.
• Comfortable coding in Python and eager to apply it for ETL automation and analytics.
• Interested in emerging technologies like Generative AI, LLM frameworks (LangChain, LangGraph), and Marimo notebooks.
• Detail-oriented, analytical, and self-motivated with strong problem-solving skills.
• Good communication and teamwork abilities.

• Pursuing a degree in Computer Science, Software Engineering, Information Systems, or related field.
• Experience (academic or project-based) with ETL pipelines in Oracle/Postgres
• Familiarity with Generative AI frameworks (LangChain, LangGraph, Chainlit, or similar).
• Knowledge of version control (Git) and Agile practices.

Our Woodlands site is one of the largest electronics manufacturing sites in Singapore, housing our recording media operations. Spread over three sites, it is easily accessible via bus or from the MRT Station, with many employees taking mass transportation to work. Here at work, you can enjoy breakfast, lunch, dinner, and snacks at our onsite canteen and coffee shop. We offer a range of facilities including an in-house gym and dance studio, as well as after-work badminton and table tennis competitions. On-site celebrations and community volunteer opportunities also abound.

Location: Woodlands, Singapore, W2

Travel: None

• Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Engineering, or a related field.
• Experience as a Data Analyst or in a similar analytical/data science role.
• Strong proficiency in SQL for data querying and transformation.
• Advanced knowledge of Python for data analysis, automation, and ML workflows.
• Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• Solid understanding of data validation, anomaly detection, and data quality principles .
• Hands-on experience with data visualization and reporting tools (e.g., Power BI, Tableau, Matplotlib, Seaborn).
• Familiarity with version control (Git), Jupyter notebooks, and working in collaborative environments.

The Engineering Lead Analyst is a senior level position responsible for leading a variety of engineering activities including the design, acquisition and deployment of hardware, software and network infrastructure in coordination with the Technology team. The overall objective of this role is to lead efforts to ensure quality standards are being met within existing and planned framework.

Responsibilities:

• Strategic Leadership: Define and execute the data engineering roadmap for Global Wealth Data, aligning with overall business objectives and technology strategy. This includes understanding the data needs of portfolio managers, investment advisors, and other stakeholders in the wealth management ecosystem.
• Team Management: Lead, mentor, and develop a high-performing, globally distributed team of data engineers, fostering a culture of collaboration, innovation, and continuous improvement.
• Architecture and Design: Oversee the design and implementation of robust and scalable data pipelines, data warehouses, and data lakes, ensuring data quality, integrity, and availability for global wealth data. This includes designing solutions for handling large volumes of structured and unstructured data from various sources.
• Technology Selection and Implementation: Evaluate and select appropriate technologies and tools for data engineering, staying abreast of industry best practices and emerging trends specific to wealth management data.
• Performance Optimization: Continuously monitor and optimize data pipelines and infrastructure for performance, scalability, and cost-effectiveness, ensuring optimal access to global wealth data.
• Collaboration: Partner with business stakeholders, data scientists, portfolio managers, and other technology teams to understand data needs and deliver effective solutions that support investment strategies and client reporting.
• Data Governance: Implement and enforce data governance policies and procedures to ensure data quality, security, and compliance with relevant regulations, particularly around sensitive financial data.

Qualifications:

• 10-15 years of hands-on experience in Hadoop, Scala, Java, Spark, Hive, Kafka, Impala, Unix Scripting and other Big data frameworks.
• 4+ years of experience with relational SQL and NoSQL databases: Oracle, MongoDB, HBase
• Strong proficiency in Python and Spark Java with knowledge of core spark concepts (RDDs, Dataframes, Spark Streaming, etc) and Scala and SQL
• Data Integration, Migration & Large Scale ETL experience (Common ETL platforms such as PySpark/DataStage/AbInitio etc.) - ETL design & build, handling, reconciliation and normalization
• Data Modeling experience (OLAP, OLTP, Logical/Physical Modeling, Normalization, knowledge on performance tuning)
• Experienced in working with large and multiple datasets and data warehouses
• Experience building and optimizing 'big data' data pipelines, architectures, and datasets.
• Strong analytic skills and experience working with unstructured datasets
• Ability to effectively use complex analytical, interpretive, and problem-solving techniques
• Experience with Confluent Kafka, Redhat JBPM, CI/CD build pipelines and toolchain – Git, BitBucket, Jira
• Experience with external cloud platform such as OpenShift, AWS & GCP
• Experience with container technologies (Docker, Pivotal Cloud Foundry) and supporting frameworks (Kubernetes, OpenShift, Mesos)
• Experienced in integrating search solution with middleware & distributed messaging - Kafka
• Highly effective interpersonal and communication skills with tech/non-tech stakeholders.
• Experienced in software development life cycle and good problem-solving skills.
• Excellent problem-solving skills and strong mathematical and analytical mindset
• Ability to work in a fast-paced financial environment

Education:

• Bachelor's degree/University degree or equivalent experience
• Master's degree preferred

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Job Family Group:

Technology

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Job Family:

Systems & Engineering

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Time Type:

Full time

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Most Relevant Skills

Please see the requirements listed above.

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Other Relevant Skills

For complementary skills, please see above and/or contact the recruiter.

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Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.

If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi .

View Citi's EEO Policy Statement and the Know Your Rights poster.

We are seeking a highly proficient and results-driven Data Engineering Architect with a robust background in designing, implementing, and maintaining scalable and resilient data ecosystems. The ideal candidate will possess a minimum of five years of dedicated experience in orchestrating complex data workflows and will serve as a key contributor within our advanced data services team. This role requires a meticulous professional who can transform intricate business requirements into high-performance, production-grade data solutions.

• Architectural Stewardship: Design, develop, and optimize sophisticated data pipelines leveraging distributed computing frameworks to ensure efficiency, reliability, and scalability of data ingestion, transformation, and delivery layers.
• SQL Mastery: Act as a subject matter expert in SQL, crafting and refining highly complex, multi-layered queries and stored procedures for advanced data manipulation, extraction, and reporting, while ensuring optimal performance and resource utilization.
• Distributed Processing Expertise: Lead the development and deployment of data processing jobs using Apache Spark , orchestrating complex data transformations, aggregations, and feature engineering at petabyte-scale.
• Big Data Orchestration: Proactively manage and evolve our data warehousing solutions built on Apache Hive , overseeing schema design, partition management, and query optimization to support large-scale analytical and reporting needs.
• Collaborative Innovation: Work synergistically with senior engineers and cross-functional teams to conceptualize and execute architectural enhancements, data modeling strategies, and systems integrations that align with long-term business objectives.
• Quality Assurance & Governance: Establish and enforce rigorous data quality standards, implementing comprehensive validation protocols and monitoring mechanisms to guarantee data integrity, accuracy, and lineage across all systems.
• Operational Excellence: Proactively identify, diagnose, and remediate technical bottlenecks and anomalies within data workflows, ensuring system uptime and operational stability through systematic troubleshooting and root cause analysis.

• Educational Foundation: Bachelor's degree in Computer Science, Information Systems, or a closely related quantitative field.
• Experience: A minimum of five (5) years of progressive, hands-on experience in a dedicated data engineering or equivalent role, with a proven track record of delivering enterprise-level data solutions.
• Core Technical Skills:
  
  SQL: Expert-level proficiency in SQL programming is non-negotiable, including advanced query optimization, window functions, and schema design principles.

Distributed Computing: Demonstrated high-level proficiency with Apache Spark for large-scale data processing.

Data Warehousing: In-depth, practical experience with Apache Hive and its ecosystem.
- Conceptual Knowledge: Deep understanding of data warehousing methodologies, ETL/ELT processes, and dimensional modeling.
- Analytical Acumen: Exceptional problem-solving and analytical capabilities, with the ability to dissect complex technical challenges and formulate elegant, scalable solutions.
- Continuous Learning: A relentless curiosity and a strong desire to stay abreast of emerging technologies and industry best practices.
- Domain Preference: Prior professional experience within the Banking or Financial Services sector is highly advantageous.

1. Data Engineering & Platform Knowledge (Must)

• Strong understanding of Hadoop ecosystem: HDFS, Hive, Impala, Oozie, Sqoop, Spark (on YARN).

• Experience in data migration strategies (lift & shift, incremental, re-engineering pipelines).

• Knowledge of Databricks architecture (Workspaces, Unity Catalog, Clusters, Delta Lake, Workflows).

2. Testing & Validation (Preferred)

• Data reconciliation (source vs. target).

• Performance benchmarking.

• Automated test frameworks for ETL pipelines.

3. Databricks-Specific Expertise (Preferred)

• Delta Lake: ACID transactions, time travel, schema evolution, Z-ordering.

• Unity Catalog: Catalog/schema/table design, access control, lineage, tags.

• Workflows/Jobs: Orchestration, job clusters vs. all-purpose clusters.

• SQL Endpoints / Databricks SQL: Designing downstream consumption models.

• Performance Tuning: Partitioning, caching, adaptive query execution (AQE), photon runtime.

4. Migration & Data Movement (Preferred)

• Data migration from HDFS/Cloudera to cloud storage (ADLS/S3/GCS).

• Incremental ingestion techniques (Change Data Capture, Delta ingestion frameworks).

• Mapping Hive Metastore to Unity Catalog (metastore migration).

• Refactoring HiveQL/Impala SQL to Databricks SQL (syntax differences).

5. Security & Governance (Nice to have)

• Mapping Cloudera Ranger/SSO policies Unity Catalog RBAC.

• Azure AD / AWS IAM integration with Databricks.

• Data encryption, masking, anonymization strategies.

• Service Principal setup & governance.

6. DevOps & Automation (Nice to have)

• Infrastructure as Code (Terraform for Databricks, Cloud storage, Networking).

• CI/CD for Databricks (GitHub Actions, Azure DevOps, Databricks Asset Bundles).

• Cluster policies & job automation.

• Monitoring & logging (Databricks system tables, cloud-native monitoring).

7. Cloud & Infra Skills (Nice to have)

• Strong knowledge of the target cloud (AWS/Azure/GCP):

o Storage (S3/ADLS/GCS).

o Networking (VNETs, Private Links, Security Groups).

o IAM & Key Management. 9. Soft Skills

• Ability to work with business stakeholders for data domain remapping.

• Strong documentation and governance mindset.

• Cross-team collaboration (infra, security, data, business).

Company description:

Changi Airport Group (CAG) is the manager of Singapore Changi Airport, a leading air hub in Asia and one of the world's most awarded airports. As airport manager, CAG performs the key functions of airport operations, air hub development, retail and commercial activities, infrastructure development and airport emergency services. CAG also manages Seletar Airport, and through its subsidiary, Changi Airports International, it takes Changi's presence beyond Singapore's shores through consultancy projects and investments in foreign airports. Come join us today

Job description:

Changi Airport Group (CAG) is seeking dynamic and motivated individuals to join the Innovation and Process Enhancement team within the Engineering & Development Cluster (E&D). As a key player in the aviation industry, CAG is committed to leveraging cutting-edge technologies and fostering creativity to enhance engineering systems and processes, ultimately contributing to the continuous improvement of the airport experience.

As a Data & IoT Engineer at CAG E&D, you will play a crucial role in developing digital solutions for asset management transformation and digital twins. Join our in-house software development and maintenance team to formulate strategies, design architectures, and implement innovative solutions utilising IoT, data analytics, and predictive maintenance capabilities. Additionally, you will conduct engineering innovation trials and explore new technologies to improve operations and maintenance outcomes.

Key Responsibilities:

• Work with our engineering system maintenance teams to install sensors for data acquisition, apply engineering/ asset management fundamentals and data engineering and analytics techniques for real-time condition monitoring and to achieve predictive maintenance.
• Formulate strategies and architecture, and propose/ review technical requirements for IoT management, engineering data management, and visualisation to support the implementation of planned smart initiatives (e.g. digital tools, digital twins), ensuring compliance with cybersecurity requirements.
• Manage, maintain, and optimise the performance of E&D's common IoT, data storage, and visualisation platforms for non-proprietary engineering systems.
• Onboard sensors, program controllers, configure IoT platform, clean incoming sensor data, manage API, process and analyse data, draw insights, develop and configure engineering systems' graphic user interface/ dashboard, conduct testing and quality assurance.
• Consult internal and external stakeholders, formulate cluster-wide strategies/ policies, develop and validate use cases and hypotheses, propose and test ideas, and implement engineering innovation projects.
• Contribute to E&D's Innovation Programme Management Office by strategising, planning, organising events/ programs, and driving innovation efforts within E&D and with the corporate innovation team.

Requirements:

• Good degree in Engineering or related disciplines.
• Proven experience in IoT platform management and cloud services (AWS), with a focus on IoT, data analytics, and engineering data management.
• Strong proficiency in back-end languages and frameworks (e.g. C#, Python) and database management (e.g. PostgreSQL, MySQL).
• Knowledge of front-end languages, libraries and frameworks (e.g. HTML/ CSS, JavaScript, XML, React, Angular, jQuery) and visualisation tools (e.g. OutSystems, Splunk) is a plus.
• Familiarity with asset management, digital twins, and predictive maintenance concepts.
• Understanding of cybersecurity principles and the ability to implement secure solutions.
• Excellent problem-solving skills and the ability to work independently or collaboratively within a team.
• Proactive mindset and a passion for innovation in technology, programming, sensor instrumentation, and solution integration.
• Strong communication skills, both written and verbal.
• Prior experience in the aviation or transportation industry is a plus.

If you are ready to be part of a forward-thinking team that shapes the future of airport engineering, we invite you to apply and contribute to CAG's commitment to excellence and innovation.

SPH Media's mission is to be the trusted source of news on Singapore and Asia, to represent the communities that make up Singapore, and to connect them to the world.

It has several business segments in the media industry, including the publishing of newspapers, magazines, and books in both print and digital editions. It also owns and operates other businesses including radio stations and outdoor media.

• Data Pipeline & Architecture
• Design, build, and optimize scalable, reliable data pipelines (batch and streaming) and ETL/ELT workflows using SQL, Python, and big data technologies.
• Lead data architecture discussions, including the design and review of ERDs, data models, and system design.
• Build and maintain transactional and analytical schemas for data lakes, warehouses, and marts.
• Cloud & Infrastructure
• Implement and manage cloud-based data platforms (AWS preferred; Azure/GCP experience a plus) ensuring scalability, reliability, cost efficiency, and security.
• Deploy and manage infrastructure using Terraform and other IaC tools.
• Develop and maintain CI/CD pipelines (e.g., GitHub Actions) for deploying data applications and services.
• Apply best practices for cloud infrastructure, including cost management, security, redundancy, and performance optimization.
• Data Quality, Governance & Security
• Drive data quality, governance, and compliance across product and business areas.
• Implement data encryption, hashing, and privacy protection mechanisms.
• Adhere to Master Data Management (MDM) principles and enterprise data governance policies.
• Analytics & Business Impact
• Partner with product, engineering, data science, and business teams to deliver business outcomes through data-driven products.
• Deliver audience and behavioral analytics, KPIs, dashboards, and reporting.
• Propose solutions for BI dashboards and enterprise data needs.
• Support the democratization of data across the organization.
• Leadership & Collaboration
• Lead a team of data engineers, taking ownership of decisions and deliveries.
• Mentor and guide engineers in best practices, architecture, and performance optimization.
• Manage stakeholder relationships, roadmaps, and expectations.
• Work with diverse stakeholders across domains including sales, marketing, advertising, engineering, and publishing.
• Follow Agile methodologies (Scrum) for project delivery.

• Strong proficiency in SQL for data modeling, querying, and transformation.
• Advanced Python development skills for data engineering use cases.
• Proven experience in AWS services (S3, Glue, Lambda, RDS, Lake Formation, Athena, Kinesis, EMR, Step Functions).
• Strong expertise in Terraform for infrastructure provisioning.
• Proficiency in CI/CD tools (e.g., GitHub Actions) and Git branching strategies.
• Hands-on experience with big data technologies such as Spark, Hive, Kafka, Hudi, or Iceberg.
• Ability to design BI-ready data models (dimensional modeling) and implement BI frameworks.
• Solid understanding of data governance, data quality, and security frameworks .
• Strong communication skills to explain complex data and analytics concepts to stakeholders.
• Leadership experience, including mentoring teams and managing deliveries.

• 7+ years of relevant hands-on experience in data engineering, solution architecture, or analytics roles.
• 5+ years of team leadership or people management experience.
• Experience with containerization and orchestration (Docker, Kubernetes).
• Experience with BI tools (Tableau, QuickSight, etc.) and query engines (Presto, Trino).
• Familiarity with Agile methodologies and enterprise-scale data platform implementations.

We are seeking a highly skilled and experienced Cloud Data Engineering Lead to spearhead our cloud-based data initiatives. You will be responsible for architecting, building, and maintaining scalable data pipelines and platforms in the cloud, enabling advanced analytics and data-driven decision-making across the organization.

Key Responsibilities:

• Leadership & Strategy
• Lead a team of data engineers in designing and implementing cloud-native data solutions.
• Define and drive the data engineering roadmap aligned with business goals.
• Collaborate with cross-functional teams, including Data Science, Analytics, DevOps, and Product.
• Architecture & Development
• Architect and implement scalable, secure, and cost-effective data pipelines and platforms.
• Design and optimize data lake, data warehouse, and real-time streaming architectures.
• Ensure high availability, performance, and reliability of data systems.
• Cloud & Tools
• Leverage cloud platforms (AWS, Azure). for data storage, processing, and orchestration.

Utilize tools such as Snowflake, Data Bricks, AWS Glue, Iceberg, Apache Spark, Airflow, Kafka, dbt, and Terraform.

• Implement CI/CD pipelines and infrastructure-as-code for data workflows.
• Governance & Quality
• Establish data governance, security, and compliance standards.
• Monitor data quality and implement automated validation and alerting mechanisms.
• Mentorship & Growth
• Mentor junior engineers and foster a culture of continuous learning and innovation.
• Conduct code reviews, technical workshops, and performance evaluations.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Engineering, or related field.
• 7+ years of experience in data engineering, with 2+ years in a leadership role.
• Proven expertise in cloud platforms (AWS, Azure).
• Strong programming skills in Python, Scala, or Java.
• Experience with big data technologies (Spark, Hadoop), ETL tools, and SQL.
• Familiarity with data modeling, warehousing, and real-time data processing.
• Excellent communication, leadership, and project management skills.

5 day week @ AMK area

Maestro HR

damien lee tian hong

R

16C8462

We are seeking a highly skilled and experienced Cloud Data Engineering Lead to spearhead our cloud-based data initiatives. You will be responsible for architecting, building, and maintaining scalable data pipelines and platforms in the cloud, enabling advanced analytics and data-driven decision-making across the organization.

Key Responsibilities:

· Leadership & Strategy

· Lead a team of data engineers in designing and implementing cloud-native data solutions.

· Define and drive the data engineering roadmap aligned with business goals.

· Collaborate with cross-functional teams including Data Science, Analytics, DevOps, and Product.

· Architecture & Development

· Architect and implement scalable, secure, and cost-effective data pipelines and platforms.

· Design and optimize data lake, data warehouse, and real-time streaming architectures.

· Ensure high availability, performance, and reliability of data systems.

· Cloud & Tools

· Leverage cloud platforms (AWS, Azure). for data storage, processing, and orchestration.

Utilize tools such as Snowflake, Data Bricks, AWS Glue, Iceberg, Apache Spark, Airflow, Kafka, dbt, and Terraform.

· Implement CI/CD pipelines and infrastructure-as-code for data workflows.

· Governance & Quality

· Establish data governance, security, and compliance standards.

· Monitor data quality and implement automated validation and alerting mechanisms.

· Mentorship & Growth

· Mentor junior engineers and foster a culture of continuous learning and innovation.

· Conduct code reviews, technical workshops, and performance evaluations.

Qualifications:

· Bachelor's or Master's degree in Computer Science, Engineering, or related field.

· years of experience in data engineering, with 2+ years in a leadership role.

· Proven expertise in cloud platforms (AWS, Azure).

· Strong programming skills in Python, Scala, or Java.

· Experience with big data technologies (Spark, Hadoop), ETL tools, and SQL.

· Familiarity with data modeling, warehousing, and real-time data processing.

· Excellent communication, leadership, and project management skills.

Maestro HR

damien lee tian hong

R

16C8462