Lead Analytics Engineer (Databricks | Lakehouse | Data Modelling)
Role details
Job location
Tech stack
Job description
Location: London, United Kingdom (Hybrid: 3 days onsite per week)
Employment Type: Full-time/Permanent
We're looking for a Lead Analytics Engineer to join a fast-growing AI & Data team, where you'll play a critical role in shaping how data drives executive decision-making.
You will own the analytics layer, design scalable data models, and transform raw data into trusted, business-ready insights.
If you enjoy working with Databricks, modern lakehouse architectures, and data modelling, this role is for you.
Key Responsibilities
- Architect and build scalable data pipelines on Databricks
- Design and implement data models (Star Schema, Facts & Dimensions)
- Own the semantic/analytics layer ( single source of truth )
- Work with Delta Live Tables, Unity Catalog, Workflows
- Optimize and troubleshoot complex ETL pipelines
- Collaborate with business and technical teams to deliver impactful insights
- Drive best practices across data architecture & engineering
What We're Looking For
- Strong hands-on experience with Databricks (Spark, Delta Lake)
- Advanced SQL + Python (Databricks Notebooks, Pandas)
- Proven experience in data modelling (Star Schema, SCD, CDC)
- Experience building data warehouses/lakehouses
- Good understanding of Medallion Architecture
- Experience with Azure DevOps/CI-CD pipelines
- Ability to translate data into business value
Nice to Have
- Azure certifications (AZ-900, DP-203, DP-500)
- Databricks certifications
- Exposure to Microsoft Fabric
- Experience with AI-assisted development tools
How to Apply:
Send your CV highlighting hands-on experience in Databricks Lakehouse Architect + Data Modeller.
Requirements
- Strong hands-on experience with Databricks (Spark, Delta Lake)
- Advanced SQL + Python (Databricks Notebooks, Pandas)
- Proven experience in data modelling (Star Schema, SCD, CDC)
- Experience building data warehouses/lakehouses
- Good understanding of Medallion Architecture
- Experience with Azure DevOps/CI-CD pipelines
- Ability to translate data into business value
Nice to Have
- Azure certifications (AZ-900, DP-203, DP-500)
- Databricks certifications
- Exposure to Microsoft Fabric
- Experience with AI-assisted development tools