Statista

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

Hamburg or Berlin, Germany full-time Mid Salary not listed
full-time Mid level Technology & IT Curated
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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
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.

What you’ll do
Own and manage tracking data pipelines and infrastructure (event data, web tracking)

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

Build and optimize ELT pipelines using Python and SQL

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

Support the shift toward streaming and modern analytics use cases

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

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

Your profile
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

What success looks like
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

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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Interview prep

Walk in with sharper answers.

Use this as a quick practice sheet before you speak with the employer.

Mid
Technology & IT Data Analysis MySQL Python SQL Writing Mid level

Likely questions

  1. Tell us about work you have done that is close to the Data Engineer - Tracking Infrastructure (m/f/d) role.
  2. How would you approach your first 30 days at Statista?
  3. Which of Data Analysis, MySQL and Python have you used recently, and what did it help you achieve?
  4. Describe a time you solved a problem without waiting to be told exactly what to do.
  5. How do you handle busy days, changing priorities, or pressure at work?

Prepare before the call

  • A recent example that proves your experience with Data Analysis, MySQL and Python.
  • One short story with a problem, your action, and the result.
  • Two examples that show the strengths listed on your CV.
  • A clear reason why this role and company interest you.
  • Your availability, preferred work style, and salary expectations.

Ask them

  • What would success look like in the first 90 days?
  • What are the main problems this hire should help solve?
  • How does the team give feedback and measure good work?
  • What does a normal working week look like for this role?
Practice line

I am interested in the Data Engineer - Tracking Infrastructure (m/f/d) role because I can bring practical experience in Data Analysis, MySQL and Python, learn the team quickly, and contribute to the outcomes Statista needs from this hire.

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