Data Engineering Manager

Key Responsibilities

• Lead and mentor a team of data engineers, fostering technical growth and accountability
• Design and oversee data pipeline architecture from ingestion through delivery, ensuring scalability and reliability
• Own data quality, cleaning, ETL processes, and delivery mechanisms serving analytics and ML/AI operations
• Collaborate with data science and MLOps teams to support model development and production deployment
• Stay current with data engineering best practices and emerging technologies; drive technical decision-making

Required Experience

• 4+ years in a team lead, principal engineer, or management role leading engineers (local and/or remote teams)
• 5+ years as a hands-on data engineer with recent, demonstrated experience in modern tech stacks
• Direct experience in change management, scaling teams, remote / hybrid / onsite team coordination
• Significant production experience with the Databricks Lakehouse on AWS — Unity Catalog, Delta Live Tables, Databricks SQL, and Databricks Workflows. Working knowledge of supporting AWS services (S3, IAM)
• Deep expertise in data pipeline design, ingestion, transformation, quality assurance, and delivery
• Professional experience in data-driven organizations with insights and ML/AI as core business functions
• Hands-on FinOps — owning compute spend, building cost visibility, and driving cost-optimization initiatives
• Working knowledge of data science, ML/AI operations, and model deployment pipelines

Preferred Qualifications

• Production AI/ML systems experience where data engineering directly enabled product features
• Experience managing teams across multiple time zones or geographic locations
• Familiarity with data governance, compliance, and metadata management at scale
• Track record of building and scaling data platforms that support analytics and operational intelligence

What we offer

• Cafeteria package and Medicover private healthcare
• Hybrid working model
• Opportunity to shape and grow a newly building team
• International environment and collaboration across global teams
• Close collaboration with a recognized US-based AI expert
• Modern, AI-focused technology environment
• High level of ownership and the opportunity to make a real impact on the data platform and engineering organization