p /pp /pp style=text-align:justify /pp style=text-align:justifyspan style=font-family:arial, helvetica, sans-serifstrongWe are looking for a /strong/span/pp style=text-align:justifyspan style=font-family:arial, helvetica, sans-serifstrongData Engineering Lead (m/w/d)/strong/span/pp style=text-align:justifyspan style=font-family:arial, helvetica, sans-serifstrong(unlimited, full-time) Join our team at our location in Berlin, Verl, Baden-Baden or Oslo – hybrid working conditions available. /strong/span/pp style=text-align:justify /pp style=text-align:justifyspan style=font-family:arial, helvetica, sans-serifstrong(Y)our Mission:/strong/span/pp style=text-align:justify /pdiv style=text-align:justifypspan style=font-family:arial, helvetica, sans-serifThe 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. /span/p/divdiv style=text-align:justifypspan style=font-family:arial, helvetica, sans-serifWorking 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. /span/p/divp style=text-align:justify /pp style=text-align:justifyspan style=font-family:arial, helvetica, sans-serifstrongYour key responsibilities:/strong/span/pp style=text-align:justify /pp style=text-align:justifyspan style=font-family:arial, helvetica, sans-serifStrategic Leadership /span/pul style=text-align:justifyli style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifDefine and execute the data engineering vision and roadmap aligned with the overall Data, AI amp; Analytics strategy. /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifEstablish and continuously improve the operating model for data engineers within agile data product teams, ensuring clear accountability for delivery outcomes (timeliness, quality, completeness, compliance). /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifChampion 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. /span/li/ulp style=text-align:justify /pp style=text-align:justifyspan style=font-family:arial, helvetica, sans-serifData Pipelines amp; Modeling /span/pul style=text-align:justifyli style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifOversee the development of robust ETL/ELT pipelines to ingest and transform data from multiple internal and external sources. /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifEnsure that agile data product teams deliver fit-for-purpose data models that meet the needs of analytics, AI, and regulatory reporting. /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifDrive excellence in data modeling and pipeline design, ensuring solutions are efficient, maintainable, and well-documented. /span/li/ulp style=text-align:justify /pp style=text-align:justifyspan style=font-family:arial, helvetica, sans-serifData Quality amp; Reliability /span/pul style=text-align:justifyli style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifImplement data quality frameworks and automation across pipelines owned by agile teams. /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifDefine and monitor data SLAs and SLOs, ensuring that product teams deliver data that meets business needs in terms of timeliness, accuracy, and availability. /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifPromote proactive data reliability engineering, enabling teams to detect and resolve issues early. /span/li/ulp style=text-align:justify /pp style=text-align:justifyspan style=font-family:arial, helvetica, sans-serifCollaboration amp; Stakeholder Management /span/pul style=text-align:justifyli style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifCollaborate closely with Data Product Owners to prioritize and deliver data engineering work in alignment with business priorities. /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifPartner with Platform Engineering teams to ensure smooth operation of data pipelines within the shared core data platform. /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifCollaborate with the Business IT teams to create reliable and robust interfaces to the source systems /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifWork hand-in-hand with Data Governance and Data Architecture to ensure alignment on metadata, lineage, and data ownership. /span/li/ulp style=text-align:justify /pp style=text-align:justifyspan style=font-family:arial, helvetica, sans-serifTeam Leadership amp; Development /span/pul style=text-align:justifyli style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifLead, mentor, and grow a high-performing team of data engineers working across multiple agile data product teams. /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifEnsure consistent technical standards, delivery practices, and performance management across the discipline, even within decentralized team setups. /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifCultivate a culture of ownership, accountability, and collaboration within and across agile data product teams. /span/li/ulp style=text-align:justify /pp style=text-align:justifyspan style=font-family:arial, helvetica, sans-serifProcess amp; Operational Excellence /span/pul style=text-align:justifyli style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifPromote automation, CI/CD for data, and observability across all data engineering workstreams, including AI-based productivity increases. /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifEstablish KPIs for engineering productivity, pipeline performance, and data delivery quality within product teams. /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifContribute to the evolution of our data-as-a-product approach, ensuring data products are discoverable, well-documented, and reusable. /span/li/ulp style=text-align:justify /pp style=text-align:justifyspan style=font-family:arial, helvetica, sans-serifstrongWhat you bring:/strong/span/pp style=text-align:justify /pul style=text-align:justifyli style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serif10+ years of experience in data engineering, with at least 3–5 years in a leadership role managing multi-team delivery, with overall team size gt;10 /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifProven success in leading data engineering functions within agile, cross-functional data product teams. /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifStrong technical expertise in Azure, SQL, Python, and modern data transformation and orchestration frameworks (e.g., dbt, Airflow, Spark) /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifDeep experience with cloud-based data lakehouses (Azure cloud, Databricks Medallion architecture) /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifExperience in fintech or financial services is a strong advantage. /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifExpertise in data modeling, transformation, and quality assurance for analytical and operational use cases. /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifStrong knowledge of data architecture principles and data product thinking. /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifExcellent communication and stakeholder management skills — especially in cross-functional agile environments. /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifLeadership skills to manage distributed teams and ensure accountability for delivery outcomes. /span/lili style=font-family:arial, helvetica, sans-serifspan style=font-family:arial, helvetica, sans-serifBachelor’s or Master’s degree in Computer Science, Data Engineering, Information Systems, or a related field. /span/li/ulp style=text-align:justify /pp style=text-align:justifyspan style=font-family:arial, helvetica, sans-serifPlease note: we do not provide visa sponsorship, you need to have EU citizenship and/or a valid work permit for Germany/Norway. /span/pp style=text-align:justify /pp /pp /p