Data Engineering Lead (m/w/d)
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.