Data Engineer - Modelled Data (m/f/d)

Statista WorkFromHome

Stellenbeschreibung:

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

Develop tools that enable large‑scale forecasting and modelling of market sizes, market shares, and other key indicators across Statista’s market insights coverage.
Leverage AI and automation to support complex quantitative and qualitative analyses, helping analysts focus on interpretation and strategic insights.
Build and maintain the infrastructure required to make these tools accessible to analysts, ensuring scalability, reliability, and seamless integration into Statista’s data architecture and platform.
Enable Statista to introduce innovative data offerings that are highly relevant for our customers by integrating forecasts, survey data, financial filings, and third‑party datasets into robust pipelines and storage solutions.
Work closely with analysts, researchers, and other Data Operations teams to deliver solutions that raise efficiency, improve data quality, and expand the value of our data products.

Your Skills

Comfortable developing in Python, with experience in building scalable data pipelines, automation, and backend services.
Solid understanding of data modelling and architecture, with a strong interest in applying and promoting best practices.
Commitment to code quality and maintainability, including modular design, refactoring, code review best practices, and thorough documentation.
Ability to translate business needs into standardized, automated workflows through process mapping and optimization.
Proficiency with workflow orchestration, containerization, and version control tools (e.g., Apache Airflow, Docker, Git).
Hands‑on experience with cloud services and infrastructure (preferably AWS: ECS, EC2, EKS); experience with Infrastructure‑as‑Code is a plus.
Excellent spoken and written English skills.