Data Engineer Manager

📋 Description

• Lead and develop a Data Engineers team focused on data and ML infrastructure.
• Define scalable cloud-based MLOps and ML lifecycle support.
• Establish the engineering foundation for ML models throughout their lifecycle.
• Oversee data pipelines, ML infrastructure, deployment, monitoring, automation, and CI/CD.
• Partner with Data Science leadership to move models to production efficiently.
• Define engineering standards, best practices, and reusable patterns for ML and data engineering.

🎯 Requirements

• Significant professional experience in Data Engineering.
• 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 and implementing production-grade MLOps practices.
• Strong understanding of model deployment, monitoring, versioning, automation, and ML lifecycle

🎁 Benefits

• Learning opportunities: Certifications in AWS, Databricks, and Snowflake; AI learning paths.
• Access to Udemy Business for courses to boost technical and soft skills.
• Mentoring and career development plans and programs.
• Company-provided equipment and flexible working options.