# Senior Data Platform Engineer (m/f/d) at Statista > Hybrid · Germany · Senior · Backend · open. Source: https://alderhq.app/jobs/ashby%3Astatista%3Aa8b60835-9fee-498a-8461-d13bfb6d42db (read 2026-11-14). ## Facts (observed) - Company: [Statista](https://alderhq.app/companies/statista) - Location text: Hamburg or Berlin - Where it can be done from (inferred): Hybrid · Germany (evidence: "Location: Hamburg or Berlin") - Posted: 2026-11-11 (3 days ago) - First seen by alder: 2026-11-11 · last verified: 2026-11-12 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/statista/a8b60835-9fee-498a-8461-d13bfb6d42db - Skills listed (inferred): Kafka, AWS, Terraform, Snowflake ## Pay and sponsorship - Posted pay: not posted - Market band for similar posted roles (Berlin, n 7): p25 €79k, median €87k, p75 €119k - Licensed UK sponsor: registered as "Statista Ltd" (checked 2026-11-09, [register](https://www.gov.uk/government/publications/register-of-licensed-sponsors-workers)) ## Description (the employer's text) 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? ### Your Role Own the platform architecture. Shape and evolve the target architecture across infrastructure utilities, data product experience and federated governance, together with Data Architecture and Product. Build the Platform-as-a-Product. A standard ingestion framework, roles and permissions, cost monitoring per product and team, and agent/AI readiness. Make governance computational. Data contracts, quality gates, lineage and policies as code, enforced in the pipeline instead of by review. Monitoring, alerting, SLAs and incident handling. Deliver data assets to consumers. Standard output ports (API, MCP server, A2A, Kafka events) and a OpenMetaData catalogue for humans and agents. Work with domain teams and stakeholders. Reference products, onboarding playbook and hands-on support for data domain teams. Bring the technical view into stakeholder discussions. ### Your Skills 5+ years in data or platform engineering Hands-on depth in Snowflake and AWS Built Infrastructure as code and CI/CD for data workloads with Terraform Built self-serve capabilities other teams use without hand-holding: templates, config-driven onboarding, clear docs, policies as code and cost governance Data governance in practice: data contracts, quality checks, lineage, access management, data catalogues Strong communication with non-engineers; comfortable defending architecture decisions in cross-team steering ### 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. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3Astatista%3Aa8b60835-9fee-498a-8461-d13bfb6d42db and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.