Senior Data Engineer -Azure / Databricks Platform (Corporate Banking)
Senior data SME designing, building, and owning data pipelines and warehouse solutions on Azure and Databricks for a corporate banking data platform — including source-to-target mapping, data modeling, SQL/Python development, performance tuning, and integrations via FTP/SFTP, MQ, and APIs.
- Compensation
- Not disclosed
- Location
- Singapore, Singapore
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 10+ years
- Category
- Data engineering
- Posted
Skills
Must have
- At least 10 years of experience in the data space, with exposure to Corporate Banking
- Technically strong in data mapping (source-to-target) and the Databricks platform — pipeline development, job/cluster management, and performance tuning
- Strong experience across SDLC phases: requirements, design, build, test, and deployment
- Strong understanding of data warehouse concepts (e.g., dimensional modeling, ETL/ELT)
- Strong working knowledge of Azure and Databricks
- Strong hands-on SQL and Python skills
- Working knowledge of integration methods: file transfer protocols (FTP/SFTP), MQ, and APIs
Nice to have
- Trade, Lending, or Payments domain exposure
Full description
Avensys is a reputed global IT professional services company headquartered in Singapore. Our service spectrum includes enterprise solution consulting, business intelligence, business process automation and managed services. Given our decade of success, we have evolved to become one of the top trusted providers in Singapore and service a client base across banking and financial services, insurance, information technology, healthcare, retail and supply chain.
We are looking for a Senior Data SME to support a data engineering initiative built on Azure and Databricks within a Corporate Banking context. The ideal candidate brings deep, hands-on technical experience in data mapping and the Databricks platform, strong SDLC and data warehouse fundamentals, and is comfortable owning data solutions end-to-end on a live banking data platform. Trade, Lending, or Payments domain exposure is a strong plus
Requirements :
- At least 10 years of experience in the data space, with exposure to Corporate Banking.
- Technically strong in data mapping (source-to-target) and the Databricks platform — pipeline development, job/cluster management, and performance tuning.
- Strong experience across SDLC phases: requirements, design, build, test, and deployment.
- Strong understanding of data warehouse concepts (e.g., dimensional modeling, ETL/ELT).
- Strong working knowledge of Azure and Databricks.
- Strong hands-on SQL and Python skills.
- Working knowledge of integration methods: file transfer protocols (FTP/SFTP), MQ, and APIs.
Key Responsibilities:
- Apply SDLC concepts to lead requirement analysis, design, build, and testing activities for data workstreams.
- Own data warehouse design and data mapping activities, including data modeling and data quality standards.
- Design, build, and optimize data pipelines on Azure and Databricks, including performance tuning and troubleshooting.
- Design and own source-to-target data mapping specifications across platform components, ensuring traceability and sign-off.
- Write and troubleshoot advanced SQL and Python scripts for data validation, transformation, and analysis.
- Drive integration design and delivery involving file transfer protocols (FTP/SFTP), MQ, and APIs between source and target systems.
- Bring Corporate Banking context to data solutioning, flagging domain-specific considerations (e.g., Trade, Lending, or Payments data) where relevant.
WHAT’S ON OFFER
You will be remunerated with an excellent base salary and entitled to attractive company benefits. Additionally, you will get the opportunity to enjoy a fun and collaborative work environment, alongside a strong career progression.