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# Analytics Engineer

- **Company:** Statista GmbH
- **Location:** Berlin, Germany
- **Experience:** Experienced
- **Salary:** €61,500.0 - €86,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, BigQuery, Cloud Database, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Data Transformation, Data Structures, Data Warehousing, Database Queries, Dimensional Modeling, Document-Oriented Databases, Snowflake, Amazon Redshift
- **Published:** August 11, 2026
- **Apply:** https://www.xing.com/jobs/berlin-analytics-engineer-157069863

## About the Role

* 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

## Description

* 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


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