Senior /Lead Data Engineer
Summary
A senior/lead data engineer in Singapore who builds governed, audit-ready batch and streaming pipelines from ERP, clinical and customer systems into a lakehouse, owns data quality, lineage and PDPA-compliant governance, and prepares AI-ready datasets, embeddings and RAG corpora using Python, SQL, dbt, Snowflake/Databricks and Airflow/Dagster.
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).
