Statista

Analytics Engineer (m/f/d)

Remote, United States remote Entry Salary not listed
remote 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?

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.
Find Jobs in Germany on Arbeitnow

Interview prep

Walk in with sharper answers.

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

Role
Technology & IT Data Analysis MySQL SQL Writing remote

Likely questions

  1. Tell us about work you have done that is close to the Analytics Engineer (m/f/d) role.
  2. How would you approach your first 30 days at Statista?
  3. Which of Data Analysis, MySQL and SQL 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 stay organised and communicate clearly when working remotely?

Prepare before the call

  • A recent example that proves your experience with Data Analysis, MySQL and SQL.
  • 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 Analytics Engineer (m/f/d) role because I can bring practical experience in Data Analysis, MySQL and SQL, learn the team quickly, and contribute to the outcomes Statista needs from this hire.

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