At Statista, we’re all about facts and data, for we are the world's leading business data platform. By providing reliable and easy-to-use data as well as various data analytics products and services, we empower people worldwide to make fact-based decisions.
Founded in Hamburg in 2007, we have quickly grown into a global company with offices in major cities such as London, New York, Berlin and Tokyo. And we still have a lot of plans. Our constant growth does not only prove our success, but also keeps creating new development and career opportunities for our employees.
We value and celebrate our diverse culture. You are welcome here for who you are, no matter where you come from, what you look like, or whether you prefer bar graphs to pie charts. Your story matters – keep writing it as part of our team.
Are you ready to join us?
Role Overview & Mission
As Head of Data Engineering, you will lead the technical strategy within our Data Production division. This division is the engine behind one of the world's largest business data platforms. Your primary objective is to build and scale the technical backbone that transforms raw information into structured, high-quality data products. You will ensure our data is automated, reliable, and ready for both customers and AI applications.
Key Responsibilities
Leadership & Team Structure: Direct a department of approximately 25 engineers through three dedicated team leads. These teams focus on Scaled Data Production (crawling, ingestion, and structuring data), Internal Tools (building systems for our research and modeling teams), and Architecture (infrastructure, databases, and taxonomy governance).
Strategic Direction & Operating Model: Define and own the technical roadmap in an OKR-driven environment. You will set ambitious objectives, manage capacity allocation, and ensure your teams align with the broader data production strategy while keeping stakeholders informed.
Technical Excellence: Maintain a hands-on approach to architecture and code quality. You will guide technical standards, evaluate engineering trade-offs, and conduct code reviews to ensure solutions are clean, scalable, and practical. You will also drive the adoption of AI capabilities like intelligent data extraction.
Cross-Functional Alignment: Partner with Product, Tech, and downstream distribution teams. You need to understand the needs of data-producing teams and ensure the data we create integrates seamlessly into our customer-facing products.
What We Are Looking For
Experience: 7+ years in Data Engineering, Data Operations, or Software Engineering, with a proven track record of leading technical teams at scale.
Product Mindset: A strong ability to treat data as a product. You genuinely care about who uses the data and how, which is fundamentally different from a pure analytics or BI perspective.
Working Style: A talent for clean, simple concepts that have practical impact. You simplify without oversimplifying, ensuring your solutions actually work in production.
Technical Skills: Deep technical proficiency in Python, PostgreSQL, AWS (ECS, EC2, EKS, S3, Lambda), Apache Airflow, Docker, and Git.
AI Expertise: Practical understanding of AI principles, including foundation models, retrieval-augmented generation (RAG), prompt engineering, and evaluation metrics.
Communication: Excellent English communication skills to effectively align stakeholders, lead cross-functional teams, and influence technical decisions.
What we offer
In addition to our great team, culture, and our shared goal of empowering people with data, there are many other things that make Statista a great place to work! Join us and benefit from:
Work from abroad up to 30 calendar days a year
Hybrid work and flex-time
International team and social events
Subsidized urban mobility and access to fitness and wellness options
Free access to Langdock and all its amazing functionalities
Career & training opportunities
Attractive locations and modern offices
Mental health support with OpenUp
Some of the benefits listed here apply only to the German entity and to Junior-level roles or above.
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