Data Engineering Manager

📋 Description

• Lead design and delivery of data pipelines and integrations.
• Own end-to-end data eng initiatives from discovery to production.
• Build and scale a high-performing engineering team.
• Architect platform-agnostic pipelines, modeling, and high-volume systems.
• Guide latency, throughput, and integration options (APIs, batch, clean-room).
• Define data integration strategies and client tradeoffs.

🎯 Requirements

• 7+ years data engineering in production; 2+ years leadership.
• Advanced SQL with strong schema/data-model design.
• Experience with high-volume matching, deduplication, identity resolution.
• Platform-agnostic: Snowflake, Databricks, BigQuery, Redshift, etc.
• Pipeline development, performance testing, latency/throughput analysis.
• Batch and real-time data integration workflows.

🎁 Benefits

• Learning opportunities: AWS, Databricks, Snowflake certifications.
• Udemy Business access; AI learning paths; English lessons.
• Travel to conferences; mentoring and development plans.
• Flexible working options; company equipment provided.
• Location-based benefits may vary; consult recruiters.