About the role
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?
About the role
You will build the core engine that powers our rankings and benchmarks for hospitals worldwide: a versioned, fully reproducible computation layer that transforms harmonized metrics into comparable scores.
The focus of this role is algorithmic computation, mathematical correctness, and system reproducibility—web application development is a limited aspect of this system. As the senior technical owner for this area, you will design how scoring definitions, formula trees, category mappings, and peer-group logic are modeled as data and executed deterministically over time.
Key Responsibilities
Engine Architecture: Design and build the core scoring engine—a typed, versioned computation graph (DAG) executed deterministically with clear boundary contracts.
Methodology as Data: Model complex business logic (formula trees, categorical mappings, peer selection, and comparability adjustments) as versioned, declarative data structures.
Determinism & Lineage: Own system lineage, versioning, and execution auditability end-to-end, ensuring any score can be recalculated identically at any future date.
Internal Tools & API Layer: Build clean, typed services and contracts for our internal methodology workbench and downstream consumer applications.
Testing & Quality Discipline: Establish rigorous testing practices (e.g., golden file testing, property-based testing, regression validation) to prevent calculation drift.
Technical Ownership: Shape architecture, drive trade-offs between execution speed and cost, set code review standards, and mentor joining engineers.
Qualifications
Core Requirements (Must-Haves)
Graph Algorithms & Engine Concepts: Deep expertise in modeling and evaluating expression trees and dependency graphs (e.g., ASTs, DAGs, cycle detection, topological sorting, memoization, and selective recomputation).
Advanced Python & Typing Discipline: Mastery of modern Python with strict typing (mypy/pyright), explicit testing discipline, and clean packaging practices.
Deterministic System Design: Proven experience building auditable, reproducible systems using immutable execution records, versioned schemas, and explicit data lineage tracking.
Declarative Logic & Domain Modeling: Experience treating business logic as versioned data (e.g., typed schemas, expression trees, rules engines, or domain-specific configurations).
Typed API & Schema Design: Demonstrated ability to design, version, and operate production backend contracts and schemas for upstream workflow engines and downstream applications.
Nice-to-Haves (What Will Make You Stand Out)
Web Frameworks & Orchestration: Production experience with FastAPI (or similar async frameworks) and workflow tools (e.g., Dagster, Prefect, or Airflow).
Performance Profiling: Practical experience analyzing execution memory footprints, CPU profiles, or query efficiency against columnar data warehouses.
Cloud Infrastructure: Familiarity with deploying, monitoring, and operating containerized calculation microservices on AWS.
Your Profile
Degree: Bachelor's or Master's in Computer Science, Software Engineering, Applied Mathematics, or a related quantitative field.
Experience: 5+ years in backend software engineering building computation engines, rules platforms, or complex data-intensive backend systems; including a sustained period within one organization seeing a core system through build → launch → iteration.
Domain Knowledge: Healthcare or benchmarking domain experience is a plus (basic understanding of healthcare KPIs, quality metrics, or benchmarking concepts; familiarity with hospital rating systems, medical classification, or complex scoring methodologies is especially valuable).
Mindset: Strong analytical and mathematical mindset, with a proven ability to translate complex domain logic and formulas into clean, deterministic software abstractions.
Languages: Fluent in English, German is a plus.
Working Style: Highly structured, detail-oriented, and motivated to collaborate closely with methodology experts, analysts, and cross-functional engineers in an international environment.
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.
Find Jobs in Germany on Arbeitnow