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

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

Analytics Engineer

Key skills