Data & Integration Engineer - GenAI
Summary
Data & Integration Engineer supporting GenAI initiatives at a Singapore banking/financial services client's tech department: analyzing requirements, designing data flows, and reliably moving data between enterprise systems via APIs, SFTP, and batch pipelines (Informatica, Cloudera), and preparing structured/unstructured data for RAG and AI workflows — not model building.
Our client is an established banking and financial services organization in Singapore, the role will be within their technology department.
Responsibilities:We are looking for a Data & Integration Engineer who operates effectively at the intersection of system analysis, enterprise integration and data engineering to support GenAI initiatives.
The successful candidate will:
- Understand business and functional requirements
- Translate them into data flows and integration designs
- Work across upstream and downstream systems
- Ensure reliable movement, transformation and availability of data for GenAI use cases
- Develop scripts / programs to get data from different integration systems
- Develop APIs to integrated with relevant systems.
The focus is on getting data into the right place, in the right format, reliably.
What Matters Most- Strong system thinking and ability to understand end to end flows
- Ability to challenge bad designs and propose better ones
- Strong stakeholder communication
- Hands on enough to troubleshoot and implement, but not a pure coder
- Experience navigating messy enterprise ecosystems
- Analyse business/technical requirements and translate them into data flows and integration designs
- Work with upstream and downstream teams to define data contracts and interfaces
- Identify gaps, inefficiencies and risks in current data movement processes
- Propose pragmatic solutions balancing speed, quality and maintainability
- Design and implement data movement across systems using:
- APIs
- SFTP and file based transfers
- Batch pipelines
- Coordinate integrations across systems in the DataLake ecosystem (Informatica, Cloudera, etc.)
- Ensure data is correctly transformed, mapped and delivered to target systems
- Troubleshoot integration issues across environments
- Support data ingestion and preparation for GenAI use cases:
- document ingestion
- data aggregation
- enrichment and transformation
- Work with structured and unstructured data
- Ensure data is usable for downstream AI workflows (RAG, search, investigation flows)
- Work across multiple teams:
- data platforms
- application teams
- infrastructure
- security
- Support SIT, UAT and production rollouts
- Ensure integration reliability, error handling and monitoring
- Document flows, mappings and interfaces clearly
You are not asking them to build models, just make data usable for them.