Data Engineering Manager

Organisation/Department

We are seeking an experienced Manager, Data Engineering to lead a team building and scaling our Client's data infrastructure. You will combine hands-on technical expertise with strong leadership skills, managing both local and distributed teams while maintaining direct involvement in architecture decisions and technical implementation.

Job description

• 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

Requirements

• 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 costoptimization 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 Value

• Technical depth combined with leadership ability—you build systems and develop people
• Proven problem-solving and architecture design skills in complex, data-heavy environments
• Pragmatism over perfection; ability to balance technical excellence with business timelines
• Collaboration across teams and comfort partnering with analytics, data science, and engineering organizations
• Stakeholder fluency with SRE, DBA (SI: work with them also), BI/Analytics, Data Science and Product teams
• AI-leveraged delivery comfortable with the team using Claude Code, Cursor, or Databricks Genie to accelerate pipeline development

Benefits

• A unique professional challenge to taking part in building up a completely new R&D strategic hub from the ground up for a stable, market-leading enterprise.
• Manager-level benefits including an annual target bonus.
• Additional perks: a cafeteria allowance, private health insurance package
• Flexibility: Hybrid working model requiring 3 days of office presence and offering 2 days of home office.