Lead Data & Integration Engineer

Experience: 10+ YearsRole: Lead Data &Integration EngineerResponsibilities: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.This is not a pure development role. 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 casesThe 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 clearlyKey RequirementsBelow are the key skillsets that will be required for all relevant tasks mentioned:·        10 years of experience in system analysis, integration engineering, data engineering or technical delivery roles.·        Strong ability to translate requirements into system flows, data flows, interface specifications and implementation plans.·        Experience working with upstream and downstream teams to define anddeliver enterprise integrations.·        Practical experience with REST APIs, SFTP, batch processing, file based integration and data pipeline orchestration.·        Good understanding of data mapping, transformation, aggregation, reconciliation and data quality controls.·        Good SQL skills and basicto moderate Pythonskills for data handling, scripting, automation and troubleshooting.·        Exposure to Java·        Exposure to Informatica, Cloudera or similar enterprise data platforms.·        Working knowledge of Git, branching, pull requests, code reviews and controlled release practices.·        Familiarity with CI/CD, Jira, Confluence and enterprise deployment processes.·        Experience with Control M or equivalent scheduling tools.·        Familiarity with logging (OTEL) and monitoring tools such as Splunk  Elastic Stack.·        Exposure to GenAI concepts such as document ingestion, RAG, embeddingsand data preparation for AI workflows.Strong communicationskills, with the ability to challenge weak designs and coordinate acrossbusiness, application, data, infrastructure and security teamsKey Skills:·        Data Engineering, ·        System Integrations, Python, SQL