We are looking for a
Data Engineering Lead (m/w/d)
(unlimited, full-time) Join our team at our location in Berlin, Verl, Baden-Baden or Oslo – hybrid working conditions available.
(Y)our Mission:
The Data Engineering Lead leads the design, development, and delivery of high-quality data pipelines and data products that power analytics, BI, and AI across our fintech ecosystem in payments, dunning, invoicing, and collections. This leader will build and scale a high-performing data engineering team focused on transforming raw data into trusted, accessible, and reusable assets — ensuring that the broader organization can make faster and smarter decisions.
Working in an agile, cross-functional data product model, this role is accountable for the results and contributions of the data engineering discipline — ensuring that the data engineers deliver trusted, timely, and high-quality data to enable business and analytical outcomes.
Your key responsibilities:
Strategic Leadership
- Define and execute the data engineering vision and roadmap aligned with the overall Data, AI & Analytics strategy.
- Establish and continuously improve the operating model for data engineers within agile data product teams, ensuring clear accountability for delivery outcomes (timeliness, quality, completeness, compliance).
- Champion the adoption of modern data engineering and agile delivery practices, fostering close collaboration with product owners, BI, data analysis, data science, data platform, and tech teams.
Data Pipelines & Modeling
- Oversee the development of robust ETL/ELT pipelines to ingest and transform data from multiple internal and external sources.
- Ensure that agile data product teams deliver fit-for-purpose data models that meet the needs of analytics, AI, and regulatory reporting.
- Drive excellence in data modeling and pipeline design, ensuring solutions are efficient, maintainable, and well-documented.
Data Quality & Reliability
- Implement data quality frameworks and automation across pipelines owned by agile teams.
- Define and monitor data SLAs and SLOs, ensuring that product teams deliver data that meets business needs in terms of timeliness, accuracy, and availability.
- Promote proactive data reliability engineering, enabling teams to detect and resolve issues early.
Collaboration & Stakeholder Management
- Collaborate closely with Data Product Owners to prioritize and deliver data engineering work in alignment with business priorities.
- Partner with Platform Engineering teams to ensure smooth operation of data pipelines within the shared core data platform.
- Collaborate with the Business IT teams to create reliable and robust interfaces to the source systems
- Work hand-in-hand with Data Governance and Data Architecture to ensure alignment on metadata, lineage, and data ownership.
Team Leadership & Development
- Lead, mentor, and grow a high-performing team of data engineers working across multiple agile data product teams.
- Ensure consistent technical standards, delivery practices, and performance management across the discipline, even within decentralized team setups.
- Cultivate a culture of ownership, accountability, and collaboration within and across agile data product teams.
Process & Operational Excellence
- Promote automation, CI/CD for data, and observability across all data engineering workstreams, including AI-based productivity increases.
- Establish KPIs for engineering productivity, pipeline performance, and data delivery quality within product teams.
- Contribute to the evolution of our data-as-a-product approach, ensuring data products are discoverable, well-documented, and reusable.
What you bring:
- 10+ years of experience in data engineering, with at least 3–5 years in a leadership role managing multi-team delivery, with overall team size >10
- Proven success in leading data engineering functions within agile, cross-functional data product teams.
- Strong technical expertise in Azure, SQL, Python, and modern data transformation and orchestration frameworks (e.g., dbt, Airflow, Spark)
- Deep experience with cloud-based data lakehouses (Azure cloud, Databricks Medallion architecture)
- Experience in fintech or financial services is a strong advantage.
- Expertise in data modeling, transformation, and quality assurance for analytical and operational use cases.
- Strong knowledge of data architecture principles and data product thinking.
- Excellent communication and stakeholder management skills — especially in cross-functional agile environments.
- Leadership skills to manage distributed teams and ensure accountability for delivery outcomes.
- 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, you need to have EU citizenship and/or a valid work permit for Germany/Norway.