Data Engineering Lead

• 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
• 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
• 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
• 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
• 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
• 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
• 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 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
• EU citizenship and/or a valid work permit for Germany/Norway

Experience in fintech or financial services