Analytics Engineer to join the Data Platform team on-site in Berlin. Build, maintain, and optimize reliable data pipelines and transformation models using dbt and Dagster; collaborate with business stakeholders to translate data requirements into actionable solutions; contribute to centralized reporting models based on Data Vault principles; design and deliver high-quality reports and analyses in Tableau or Hex to drive key business decisions; ensure data reliability, performance, and quality across transformation layers through testing and documentation; participate in shaping technical best practices, goals, and timelines for the modern data stack.

Tech stack: AWS (S3, Redshift, Aurora, Glue, DMS, EC2, ECS, Fargate, Lambda), dbt, Dagster, Python, data ingestion/streaming (SNS, SQS, Segment, Kinesis), Terraform, Docker, GitHub, Tableau, Hex.

Your profile: 2+ years of experience as Analytics Engineer, Data Analyst, BI Developer, or similar; strong SQL with ability to write clean, optimized queries; hands-on experience with dbt, modular modeling, and testing; experience with BI tools (preferably Tableau and Hex); good communication and ability to translate analytical requirements into technical solutions; familiarity with AI-assisted development tools like GitHub Copilot or similar LLMs.

Nice-to-haves: Redshift, Data Vault, Dagster or Airflow, modern data architectures (data lakes, data lakehouses, data mesh), FinTech or banking exposure.

We welcome mid-level and senior profiles and encourage applicants even if not every qualification is met.

What we offer: diverse, ope

Analytics Engineer to join the Data Platform team on-site in Berlin. Build, maintain, and optimize reliable data pipelines and transformation models using dbt and Dagster; collaborate with business stakeholders to translate data requirements into actionable solutions; contribute to centralized reporting models based on Data Vault principles; design and deliver high-quality reports and analyses in Tableau or Hex to drive key business decisions; ensure data reliability, performance, and quality across transformation layers through testing and documentation; participate in shaping technical best practices, goals, and timelines for the modern data stack.

Tech stack: AWS (S3, Redshift, Aurora, Glue, DMS, EC2, ECS, Fargate, Lambda), dbt, Dagster, Python, data ingestion/streaming (SNS, SQS, Segment, Kinesis), Terraform, Docker, GitHub, Tableau, Hex.

Your profile: 2+ years of experience as Analytics Engineer, Data Analyst, BI Developer, or similar; strong SQL with ability to write clean, optimized queries; hands-on experience with dbt, modular modeling, and testing; experience with BI tools (preferably Tableau and Hex); good communication and ability to translate analytical requirements into technical solutions; familiarity with AI-assisted development tools like GitHub Copilot or similar LLMs.

Nice-to-haves: Redshift, Data Vault, Dagster or Airflow, modern data architectures (data lakes, data lakehouses, data mesh), FinTech or banking exposure.

We welcome mid-level and senior profiles and encourage applicants even if not every qualification is met.

What we offer: diverse, ope