Lead Data & Integration Engineer

Lead Data & Integration Engineer Important Information Location: Singapore Key Responsibilities 1. System Analysis & Design - 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 - Integration & Data Movement - 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 - Data Preparation for GenAI - 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) You are not asking them to build models, just make data usable for them. - Delivery & Coordination - 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 Key Requirements Below 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 and deliver 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 basic to moderate Python skills 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, embeddings and data preparation for AI workflows. - Strong communication skills, with the ability to challenge weak designs and coordinate across business, application, data, infrastructure and security teams. Key Domain: - Data Engineering, - System Integrations, - Python, SQL About Encora Encora is a global company that offers Software and Digital Engineering solutions. Our practices include Cloud Services, Product Engineering & Application Modernization, Data & Analytics, Digital Experience & Design Services, DevSecOps, Cybersecurity, Quality Engineering, AI & LLM Engineering, among others. At Encora, we hire professionals based solely on their skills and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality