Data Engineering Manager (Databricks)

Tasks

• Define conformed dimensions for multi market reporting
• Define validate and translate KPI requirements into data models
• Design and implement data integration and transformation pipelines
• Design build and maintain semantic layers and KPI models
• Establish data quality, validation, and monitoring frameworks
• Implement data security, access control, and governance
• Lead technical documentation and knowledge transfer
• Profile source data quality ownership and reconciliation
• Support production readiness assessments and deployment

Perks/Benefits

• AI learning paths
• Career development plans
• Company-provided equipment
• English lessons
• Flexible working options
• Learning opportunities
• Mentorship programs
• Special day rewards
• Study Plans Courses and Additional Certifications
• Travel opportunities to attend conferences
• Udemy business access

Skills/Tech-stack

Access Control | Azure Databricks | Conformed Dimensions | Data Governance | Data Lineage | Data Modeling | Data Monitoring | Data Quality | Data Reconciliation | Data Transformation | Data integration | Databricks | Databricks Metric Views | ELT | ETL | Git | KPI Development | Medallion Architecture | Metric Views | Python | SQL | Semantic Modeling | Version control