Data Engineering Manager

📋 Description

• Lead, mentor, and develop a team of Data Engineers focused on data and ML infrastructure.
• Define and implement technical approaches for scalable cloud-based MLOps.
• Establish the engineering foundation for ML models lifecycle and production readiness.
• Oversee data pipelines, ML infra, deployment processes, monitoring, automation, and CI/CD.
• Partner with Data Science leadership to move models from development to production.
• Define standards, best practices, and reusable patterns for ML and data engineering.

🎯 Requirements

• Significant professional experience in Data Engineering.
• Strong hands-on experience with cloud MLOps.
• Proven experience leading and mentoring Data Engineering teams.
• Strong understanding of cloud data architecture and ML infrastructure.
• Experience designing production-grade MLOps practices and ML lifecycle management.
• Ability to balance technical strategy with hands-on delivery and leadership.

🎁 Benefits

• Professional development and mentoring programs.
• Learning opportunities with AWS, Databricks, Snowflake.
• Access to Udemy Business and English lessons for professional growth.
• Flexible working options; company equipment provided.