Senior /Lead Data Engineer

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Description

You will build governed, audit-ready pipelines that turn fragmented client data into trusted, AI-ready assets. This is a central, load-bearing role working alongside AI Engineers and Data Scientists. Key Responsibilities Build and operate end-to-end ingestion pipelines from ERP, clinical, customer and operational systems (batch + streaming) into a governed lakehouse. Own transformation, modelling, and semantic layer to ensure consistent business logic across BI and AI. Prepare and serve AI-ready data - curated datasets, embeddings, and RAG corpora. Own data quality, master data / entity resolution, and end-to-end lineage for audit readiness. Embed governance, privacy & security by design (PDPA and APAC data residency / cross-border rules). Build reusable accelerators and set engineering standards for the practice. Must Have: 5-10 years of hands-on production data engineering, end-to-end delivery experience, and client-facing stakeholder management. Tech Stack: Expert Python & SQL, dbt, Snowflake / Databricks, Airflow / Dagster, Iceberg / Delta Lake, plus strong understanding of data governance, vector stores, and cloud ( Azure / AWS / GCP).

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