Data & Integration Engineer - GenAI

About the Client:Our client is an established banking and financial services organization in Singapore, the role will be within their technology departmentResponsibilities: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 ecosystemsKey Responsibilities 1. System Analysis & DesignAnalyse business/technical requirements and translate them into data flows and integration designsWork with upstream and downstream teams to define data contracts and interfacesIdentify gaps, inefficiencies and risks in current data movement processesPropose pragmatic solutions balancing speed, quality and maintainability2. Integration & Data MovementDesign and implement data movement across systems using: APIsSFTP and file based transfersBatch pipelinesCoordinate integrations across systems in the DataLake ecosystem (Informatica, Cloudera, etc.)Ensure data is correctly transformed, mapped and delivered to target systemsTroubleshoot integration issues across environments3. Data Preparation for GenAISupport data ingestion and preparation for GenAI use cases: document ingestiondata aggregationenrichment and transformationWork with structured and unstructured dataEnsure data is usable for downstream AI workflows (RAG, search, investigation flows)You are not asking them to build models, just make data usable for them.4. Delivery & CoordinationWork across multiple teams: data platformsapplication teamsinfrastructuresecuritySupport SIT, UAT and production rolloutsEnsure integration reliability, error handling and monitoringDocument flows, mappings and interfaces clearly