Data Modeler

Role Summary

We are looking for a Lead Analytics Engineer with strong Databricks data modelling expertise to design and own the analytics layer.

You will transform raw data into trusted, business-ready datasets by building the Gold Layer, enabling a scalable single source of truth for reporting and decision-making.

Key Responsibilities

• Design and build fact & dimension models (F&D) and semantic layers
• Develop and optimize data pipelines in Databricks
• Implement Medallion Architecture (Bronze, Silver, Gold)
• Migrate logic from Microsoft Fabric into Databricks Gold Layer
• Build and manage dbt models
• Ensure data quality, governance, and documentation
• Collaborate with stakeholders to deliver analytics-ready datasets

Required Skills

• Strong experience with Databricks, SQL, and Python (Pandas)
• Solid understanding of Spark, Delta Lake, and Databricks tools (DLT, Workflows, Unity Catalog)
• Expertise in data modelling: Star Schema, SCD, CDC
• Experience with dbt, Azure DevOps, CI/CD, and Git
• Exposure to Microsoft Fabric

Experience

• Proven background in data engineering/analytics engineering
• Experience building data pipelines, lakehouses, and BI-ready datasets

Nice to Have

• Azure certifications (AZ-900, DP-203, DP-500)
• Databricks certifications (Lakehouse Data Engineer)