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Analytics Engineer (m/f/d)

StatistaGermany

EngineeringFull time3+ yrs
Source-verified: read directly from this employer's own ashby job board, not a repost.HybridPosted (15 days ago)Last verified (today)

At a glance

Location
Germany
Workplace
Hybrid
Pay
Not published by the employer
Employment type
Full time
Experience
3+ years
Education
No degree requirement stated
Job family
Engineering
Seniority
Not stated
Posted by employer
8 October 2026
Last verified open
23 October 2026
Region and country
Germany, DE
Team
Tech
Listed via
Ashby

What the employer wrote

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, build, and optimize scalable data models using modern data stack tools (e.g., dbt, Snowflake)

- Transform raw data into clean, reliable, and well-documented datasets for analytics, reporting, and operational use

- Collaborate closely with data engineers, analysts, tracking teams, and business stakeholders to define data requirements and ensure alignment

- Implement and maintain data quality checks, testing, and monitoring to ensure accuracy and reliability

- Develop and manage semantic layers to standardize and govern key business metrics

- Improve data accessibility and usability across teams by promoting best practices and clear data structures

- Document data models, definitions, and workflows to enhance transparency and data literacy

- Contribute to data governance, harmonization, and automation initiatives, including enabling AI-driven analytics use cases

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 modern data stack tools and technologies (e.g., dbt, CI/CD) and openness to AI-assisted development workflows (e.g., Claude Code or similar)

- Experience working with cloud data warehouses (e.g., Snowflake, BigQuery, Redshift)

- 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.

Where this record came from

Read from Statista's own Ashby job board on , and last confirmed still open on . The employer published it on 8 October 2026. Jobsearch.ing did not write, edit or rank this posting, and does not vet the employer. View the original posting.

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