Lead/Senior Data Engineer
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Summary
Lead/Senior Data Engineer in Singapore (onsite) who architects and delivers Data Lake, Warehouse and Lakehouse platforms on Databricks, building scalable ETL/ELT pipelines with Spark, Delta Lake and orchestration tools, setting data modeling/governance standards, and mentoring the team. Requires 5+ years in data engineering and the ability to secure a clearance.
Role
- Lead the architecture, design and delivery of Data Lake, Data Warehouse and Lakehouse platforms, including on Databricks.
- Own and build scalable, reliable ETL/ELT pipelines and large-scale ingestion from diverse structured and unstructured sources.
- Build and manage data infrastructure on Databricks and modern data stack (Spark, Delta Lake).
- Define and drive data modeling (dimensional, Data Vault), data quality, and data governance standards across Lake and Warehouse layers.
- Optimize data processing jobs and SQL / Spark workloads for performance, reliability and cost on Databricks.
- Implement data security, access control, data lineage and compliance practices.
- Provide technical leadership, mentorship and code reviews to the team.
- Partner with analysts, data scientists and application teams to deliver trusted data products.
Requirements
- Degree in Computer Science, IT, Data Engineering or related.
- 5+ years in data engineering with experience leading projects or small teams.
- Strong in SQL, Python /Scala, and Spark on Databricks.
- Hands-on with Databricks Lakehouse platform, Delta Lake, ETL/ELT frameworks and orchestration (e.g., Airflow / Databricks Workflows).
- Proven experience building and operating Data Lakes and Data Warehouses at scale.
- Experience with relational databases, cloud platforms, and building secure, production-grade data pipelines.
- Strong ownership, problem-solving and communication skills.
- This role will need to secure a clearance, due to the sensitivity of the project.
EA Licence No: 20S0237