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Senior Data Engineer Job Opening In Singapore, Singapore – Now Hiring Opensource


Job description

Role Overview

The Senior Data Engineer is responsible for designing, building, and maintaining large-scale, secure, and high-performance data pipelines supporting critical Financial Services workloads.

The role focuses on data modernization, regulatory data aggregation, and AI/ML enablement across domains such as Core Banking, Payments, Risk, Treasury, and Regulatory Reporting.

  1. Key Responsibilities

  2. Design, implement, and optimize ETL/ELT data pipelines using Apache Spark, PySpark, Databricks, or Azure Synapse.

  3. Build and operationalize real-time streaming pipelines leveraging Kafka / Confluent / Azure Event Hubs for risk and liquidity data.

  4. Integrate and transform data across Core Banking, Trade, Payments, Treasury, CRM, and Compliance systems.

  5. Implement data quality, validation, and lineage controls using tools such as Great Expectations / Deequ / dbt tests.

  6. Develop and maintain data models and schemas (3NF, Dimensional, Data Vault 2.0).

  7. Collaborate with Security and Governance teams to implement data security, masking, encryption, and tokenization in compliance with MAS TRM / PDPA / PCI-DSS.
    Participate in data platform modernization projects (Teradata / DB2- Snowflake / Databricks / Synapse).

  8. Collaborate with Data Scientists and AI Engineers to deploy ML feature stores and model-serving pipelines.

  9. Support regulatory reporting (MAS 610/649) and Basel III/IV data flows.

  10. Maintain CI/CD pipelines for data infrastructure using Azure DevOps / Terraform / GitHub Actions.

  11. Required Technical Skills

  12. Category Tools / Technologies

  13. Languages Python, PySpark, SQL, Scala
  14. Data Platforms Azure Data Lake, Synapse, Databricks, Snowflake
  15. Orchestration Apache Airflow, Azure Data Factory, dbt
  16. Streaming Kafka, Confluent, Event Hubs
  17. Governance Apache Atlas, Azure Purview, Collibra
  18. Security Encryption, RBAC, Tokenization, Audit Logging
  19. CI/CD & IaC Terraform, Azure DevOps, GitHub Actions

  20. Experience and Qualifications

  21. 6 – 10 years of experience in data engineering, with at least 3 years in BFSI (banking, insurance, or capital markets).

  22. Proven experience building real-time and batch data pipelines on Azure or AWS.

  23. Exposure to regulatory data models (MAS 610, Basel III, IFRS 9/17, BCBS 239).

  24. Familiarity with DevOps and MLOps integration.

  25. Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field.

  26. Certifications preferred: Microsoft Azure Data Engineer Associate, Databricks Data Engineer Professional, Snowflake SnowPro Core.

  27. Key Attributes

  28. Strong analytical and problem-solving mindset.

  29. Ability to work across multi-disciplinary and geographically distributed teams.

  30. Excellent written and verbal communication skills.

  31. High accountability and ownership for quality and delivery.

Required Skill Profession

Other General


  • Job Details

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Unlock Your Senior Data Potential: Insight & Career Growth Guide


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Are You Looking for Senior Data Engineer Job?

Great news! is currently hiring and seeking a Senior Data Engineer to join their team. Feel free to download the job details.

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The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Opensource adheres to the cultural norms as outlined by Expertini.

The fundamental ethical values are:

1. Independence

2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying Singapore laws and regulations

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The average salary range for a varies, but the pay scale is rated "Standard" in Singapore. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

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Key qualifications for Senior Data Engineer typically include Other General and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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Interview Tips for Senior Data Engineer Job Success

Opensource interview tips for Senior Data Engineer

Here are some tips to help you prepare for and ace your Senior Data Engineer job interview:

Before the Interview:

Research: Learn about the Opensource's mission, values, products, and the specific job requirements and get further information about

Other Openings

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Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

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Follow Up: Send a thank-you email to the interviewer within 24 hours.

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Final Thought:

To prepare for your Senior Data Engineer interview at Opensource, research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Opensource's products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

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