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.
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.

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 transformati...