Penguin Random House is seeking a Data Engineering Lead to own the design, development, and delivery of high-quality data pipelines and data products. This role is central to powering analytics, BI, and AI across our fintech ecosystem in payments, dunning, invoicing, and collections. You will build and scale a high-performing team focused on transforming raw data into trusted, accessible assets.
What You'll Do
- 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 for 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 Business IT teams to create reliable and robust interfaces to 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.
What We're Looking For
- 10+ years of experience in data engineering.
- 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).
- 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.
Nice to Have
- Experience in fintech or financial services is a strong advantage.
Technical Stack
- Azure
- SQL
- Python
- dbt
- Airflow
- Spark
- Databricks
Team & Environment
You will lead a team of data engineers working across multiple agile data product teams, with an overall team size >10.
Work Mode
This is a hybrid position based in one of our office locations: Berlin, Verl, Baden-Baden, or Oslo.
