Data Engineering Manager (Databricks)

📋 Description

• Design, build, and maintain semantic layers and KPI models using Databricks Metric Views to
• Collaborate with business owners to translate KPI requirements into reusable data models and
• Profile source data quality, ownership, data grain, and reconciliation across enterprise source
• Design and implement data integration pipelines for AI-generated narratives and conversational
• Define conformed dimensions and multi-market data variations for reporting and analytics.
• Work with Business Analysts and AI Engineers to align KPI definitions with data structures and

🎯 Requirements

• 7+ years in Data Engineering with semantic layer and KPI/metric modeling
• Hands-on Databricks Metric Views or equivalent semantic/metric tooling
• SQL and Python proficiency for data processing and pipelines
• Cloud data platforms experience, especially Azure Databricks, ELT/ETL tooling
• Data modeling, conformed dimensions, Medallion-style architectures
• Data quality, lineage, reconciliation across multiple source systems

🎁 Benefits

• Learning opportunities and AWS, Databricks, Snowflake certifications
• Access to AI learning paths and Udemy Business
• English lessons and professional development plans
• Travel opportunities to industry conferences and client meetings
• Mentoring and career development programs
• Flexible working options; equipment provided