Data & Analytics Engineer (m/f/d)
Statista · Hamburg or Berlin
Skills in this posting
Extracted from the posting text by the instrument — the demand side, read literally.
The posting
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
Design, implement, and maintain backend services in Python that power our data access and distribution layer
Build and operate automated build, test, and deployment pipelines following CI/CD and GitOps practices, running on AWS and Kubernetes
Design and maintain data models and schemas (Avro, SQL) for our data pipelines and services, and publish them to downstream consumers via our Kafka-based distribution platform and schema registry
Build access-layer data models in our analytics environment (e.g., Snowflake) so applications can work with the data directly, including via API
Act as the coordination interface between the Data and Tech divisions, aligning priorities, schemas, and timelines across upstream and downstream teams
Your profile
3+ years of experience in analytics engineering, data engineering, or a related role.
Strong SQL skills and solid experience in data modeling (e.g., dimensional modeling, star schemas).
Hands-on experience with event streaming and message distribution, ideally Kafka, including schema management with the Kafka schema registry (Avro, Protobuf, or JSON Schema).
Experience designing data contracts and schemas between upstream producers and downstream consumers.
Experience with cloud data warehouses (e.g., Snowflake, BigQuery, Redshift) and modern data stack tools (e.g., dbt, CI/CD).
Openness to AI-assisted development workflows (e.g., Claude Code or similar).
Comfort working at the boundary of streaming/operational data and analytical data models, and building access layers that serve applications via API.
Strong attention to detail with a quality-focused and structured working style.
Interest in data governance, standards, and scalable data architecture.
Analytical mindset with strong problem-solving skills.
Excellent communication skills in English (German is a plus), with both technical and business stakeholders, combined with a solid understanding of business requirements and contexts.
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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Excerpt from the original listing. The full, current text lives at the source. Read and apply there →
The PivotHop read
- What a data engineer actually earnsmedian, seniority, by country
- Careers a data engineer can move intoevery measured route out
- Data Architect → Data Engineer48% readiness
- Data Analyst → Data Engineer29% readiness
- All open data engineer rolesthe full board
Where these skills also reach
Adjacent occupations measured from the same postings — readiness is what a data engineer’s profile already covers.
- 17 open data architect roles90% readiness from data engineer
- 250 open solutions architect roles64% readiness from data engineer
- 184 open data analyst roles60% readiness from data engineer
- 22 open database administrator roles57% readiness from data engineer
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