Data Engineering Manager

Awin is part of the Axel Springer group. Established in 2000, Awin is a company with a dynamic, social, and inclusive culture. The company operates in the Affiliate Marketing data platform domain, focusing on building scalable data solutions and supporting business goals.

Required:

• 8+ years of professional experience in data engineering, including 5+ years of people management and technical leadership experience.
• Deep understanding of Ralph Kimball dimensional modelling best practices, including star schema design and data cube modelling to support scalable analytics and reporting.
• Experience building and optimising cloud-based data platforms and scalable data pipelines that support analytical model development and AI-ready analytics.
• Experience working in cross-functional environments, collaborating closely with product teams and business stakeholders.
• Experience working with analytics and software engineering teams to build cloud-based solutions that support large-scale analytics workloads and reliable data delivery.
• Familiarity with data governance, security best practices, and compliance requirements.
• Strong knowledge of Agile delivery frameworks such as Scrum or Kanban, with the ability to shape and improve engineering processes.

Nice to have:

• Bachelor’s degree or higher in Data Science, Data Engineering, Business Intelligence, Business Administration, or a related field with a focus on data, business intelligence, or analytics.
• Strong interest in people management, including hiring, supporting career development, giving clear feedback, and handling team conflicts constructively.
• Proven experience leading and mentoring data engineers within cross-functional data and analytical teams.
• Ability to monitor individual performance, provide constructive feedback, and mediate conflicts effectively.
• A collaborative mindset, openness to feedback, and willingness to compromise to achieve the best possible outcomes.
• Eager to learn new technologies and new ways to work and open to new perspectives whilst deepening own area of expertise.

• Create autonomous, high-performing teams, ensuring their growth and engagement.
• Work closely with engineering, product, analytical engineers, and data scientists to build scalable AI-ready analytics solutions.
• Create clear ownership within the team and encourage a culture of autonomy, knowledge sharing, and continuous improvements.
• Lead the delivery of data solutions, ensuring they support business goals and follow good engineering practices.
• Partner with product owners and engineering leaders to balance effort and impact focusing on practical solutions that deliver real value.
• Aggressively remove blockers and accelerate decision-making; enforce a culture of radical ownership and end-to-end accountability.
• Serve as a proactive incident manager; ensure rapid escalation, clear communication on progress, and directional alignment with domain goals.
• Directly responsible for the development of people; set meaningful growth milestones, lead career progression conversations, and align individual success with team outcomes.