Lead/Senior Data Engineer

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.

To apply:

Please send your latest CV in MS Word format to [Confidential Information]

Appreciate the interest of all applicants however only shortlisted candidates will be notified.

EA Licence No: 20S0237