Data Engineering Manager (m/w/d)

Mission

The Data Engineering Manager will play a vital role in leading the design, development, and delivery of high-quality data pipelines and data products that drive analytics, BI, and AI across our fintech ecosystem, including payments, dunning, invoicing, and collections. This position offers an opportunity to build and scale a high-performing data engineering team dedicated to turning raw data into trusted, accessible, and reusable assets, empowering the organization to make swift and informed decisions. The role operates within an agile, cross-functional data product model, holding accountability for the data engineering team's results and ensuring the delivery of reliable, timely, and high-quality data to support business and analytical objectives.

Your Key Responsibilities:

• Strategic Leadership: Define and execute the data engineering vision, aligning it with the overall Data, AI & Analytics strategy, and continuously improve the operating model for data engineers.
• Data Pipelines & Modeling: Oversee the development of robust ETL/ELT pipelines to ingest and transform diverse data sources while driving excellence in data modeling & pipeline design.
• Data Quality & Reliability: Implement data quality frameworks and automation, ensuring data SLAs and SLOs meet business requirements.
• Collaboration & Stakeholder Management: Partner with Data Product Owners and Platform Engineering teams to deliver essential data engineering deliverables in harmony with business priorities.
• Team Leadership & Development: Mentor and cultivate a high-performing team of data engineers, ensuring consistent technical standards and fostering a culture of accountability and collaboration.
• Process & Operational Excellence: Promote automation and establish KPIs for engineering productivity, pipeline performance, and data delivery quality.

What You Bring:

• Over 10 years of experience in data engineering, with at least 3-5 years in a leadership role managing multi-team delivery (team size >10).
• Proven track record in leading data engineering teams within agile, cross-functional data product environments.
• Strong technical expertise in Azure, SQL, Python, and modern data transformation frameworks like dbt, Airflow, Spark.
• Deep familiarity with cloud-based data lakehouses (Azure cloud, Databricks Medallion architecture).
• Experience in the fintech sector or financial services is a significant plus.
• Expertise in data modeling, transformation, and quality assurance for various analytical and operational use cases.
• Solid understanding of data architecture principles and a data product mindset.
• Excellent communication and stakeholder management skills, especially in agile settings.
• Strong leadership skills to manage distributed teams and drive accountability for results.
• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems, or a related field.

Please note: we do not provide visa sponsorship; candidates must have EU citizenship and/or a valid work permit for Germany or Norway.