Data Engineering Manager (Databricks)

📋 Description

• Design, build, and maintain semantic layers and KPI models using Databricks Metric Views to
• Work directly with business owners to define, validate, and translate KPI requirements into
• Profile source data quality, ownership, data grain, and reconciliation requirements across
• Design and implement data integration and transformation pipelines that prepare enterprise data for
• Define conformed dimensions and market-specific data variations to support multi-market reporting
• Collaborate closely with Business Analysts and AI Engineers to align KPI definitions with

🎯 Requirements

• 7+ years of experience in Data Engineering, with demonstrated expertise in semantic layer and
• Strong hands-on experience building and maintaining Databricks Metric Views or equivalent
• Advanced proficiency in SQL and Python for data processing, transformation, and pipeline
• Solid understanding of cloud data platforms, specifically Azure Databricks, and modern ELT/ETL
• Demonstrated expertise in data modeling techniques, conformed dimensions, and Medallion-style
• Experience profiling data quality, lineage, and reconciliation across multiple source systems.

🎁 Benefits

• Learning Opportunities: Certifications in AWS, Databricks, Snowflake; access to AI learning paths
• Travel opportunities to attend industry conferences and meet clients.
• Mentoring and Development: Career development plans and mentorship programs.
• Celebrations & Support: Special day rewards; company-provided equipment; flexible working