Data Engineering Manager(m/w/x)

Requirements

• 8+ years professional experience in data engineering
• 5+ years people management experience
• 5+ years technical leadership experience
• Deep understanding of Ralph Kimball dimensional modelling best practices
• Star schema design
• Data cube modelling
• Experience building cloud-based data platforms
• Experience optimising cloud-based data platforms
• Experience building scalable data pipelines
• Experience optimising scalable data pipelines
• Analytical model development
• AI-ready analytics
• Experience working in cross-functional environments
• Collaboration with product teams
• Collaboration with business stakeholders
• Experience working with analytics teams
• Experience working with software engineering teams
• Building cloud-based solutions for large-scale analytics workloads
• Reliable data delivery
• Familiarity with data governance
• Familiarity with security best practices
• Familiarity with compliance requirements
• Strong knowledge of Agile delivery frameworks (Scrum or Kanban)
• Ability to shape engineering processes
• Ability to improve engineering processes
• Bachelor’s degree or higher in Data Science, Data Engineering, Business Intelligence, Business Administration, or related field (preferred)
• Strong interest in people management
• Hiring skills
• Career development support
• Clear feedback provision
• Constructive team conflict handling
• Proven experience leading data engineers
• Proven experience mentoring data engineers
• Ability to monitor individual performance
• Ability to provide constructive feedback
• Ability to mediate conflicts effectively
• Collaborative mindset
• Openness to feedback
• Willingness to compromise
• Eagerness to learn new technologies
• Openness to new ways of working
• Openness to new perspectives
• Deepening own area of expertise

Tasks

• Lead a team of 6–12 data engineers
• Guide the team technically
• Build and improve the Affiliate Marketing data platform
• Create autonomous, high-performing teams
• Ensure team growth and engagement
• Collaborate with engineers and data scientists
• Build scalable, AI-ready analytics solutions
• Establish clear team ownership
• Foster a culture of autonomy
• Promote knowledge sharing and continuous improvement
• Lead delivery of data solutions
• Ensure solutions support business goals
• Ensure good engineering practices
• Partner with product and engineering leaders
• Balance effort and impact for solutions
• Deliver real value through practical solutions
• Aggressively remove blockers
• Accelerate decision-making
• Enforce radical ownership and accountability
• Act as a proactive incident manager
• Ensure rapid incident escalation
• Communicate incident progress clearly
• Align incident resolution with domain goals
• Develop team members
• Set meaningful growth milestones
• Lead career progression conversations
• Align individual success with team outcomes
• Support hiring efforts
• Ensure team health and success
• Balance technical quality, speed, and scalability

Work Experience

Education

Languages

Tools & Technologies