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 [email protected] Appreciate the interest of all applicants; however only shortlisted candidates will be notified.

EA Licence No: 20S0237