(Senior) Data Engineer - Tracking Infrastructure (m/f/d)

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?

Join a growing data team and take ownership of our tracking data infrastructure, which captures millions of user events across our web platform every day.

You will focus on operating, improving, and scaling existing data systems, ensuring data is reliable, cost-efficient, and accessible for analytics teams.

This is a hands-on role with strong ownership and visibility across engineering and analytics.

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  Own and manage tracking data pipelines and infrastructure (event data, web tracking)

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  Ensure data quality, governance, and cost control (e.g. retention, storage optimization)

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  Build and optimize ELT pipelines using Python and SQL

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  Improve data ingestion and orchestration (Airflow, Prefect, APIs, S3, Iceberg, databases)

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  Support the shift toward streaming and modern analytics use cases

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  Collaborate with engineering teams (data producers) and analytics teams (data consumers)

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  Enable internal users by making data reliable, well-documented, and easy to use

• Experience in data engineering within cloud environments (AWS preferred)

• Strong skills in Python and SQL

• Hands-on experience with data pipelines, orchestration tools (Airflow, Prefect), and APIs

• Familiarity with large-scale data systems and event-based data (tracking, logs, or similar)

• Experience with Snowflake (or similar DWH)

• Knowledge of infrastructure as code (Terraform) and CI/CD (GitHub Actions)

• Understanding of data architecture, testing, and best practices

• Bonus: experience with DBT, streaming tools, or BI tools

• You take ownership of a high-volume data domain and keep it stable and scalable

• You improve data reliability, usability, and cost efficiency

• You collaborate effectively with both technical and non-technical stakeholders

• You bring structure to evolving systems while staying flexible in a dynamic environment