Senior Data Engineer

Our data ecosystem powers critical decisions across three distinct product squads, requiring top-tier reliability, scale, and modern modeling standards. In this role, you will be the core technical partner translating cross-functional business requirements into resilient, highly observable data pipelines across modern data warehouse environments.

You will own the end-to-end reliability, scalability, and semantic modeling of our entire analytics platform and data infrastructure.

• Design, build, and maintain scalable data ingestion pipelines and orchestration workflows using Apache Airflow and automated CI/CD.
• Model, optimize, and manage cloud data warehouses across Google BigQuery and Snowflake.
• Develop and maintain robust DBT transformations and semantic analytics layers in Looker/LookML.
• Partner directly with Product Managers, Software Engineers, and Business Analysts across three product squads to deliver resilient data solutions.
• Implement best practices for data observability, pipeline monitoring, and schema design across AWS and GCP environments.

• 5+ years of hands-on data engineering and platform development experience.
• Advanced proficiency in Python (or Go) and workflow orchestration using Apache Airflow.
• Deep expertise with DBT and cloud data warehouses like BigQuery and Snowflake.
• Proven track record building semantic models and dashboards in Looker/LookML.
• Experienced operating across AWS/GCP with strong CI/CD practices and fluent English.

The company operates with a highly supportive, low-hierarchy culture where decisions are made quickly and pragmatically. Work is flexible and output-focused with no rigid office mandate, though team members typically drop in a few times every other week based on personal preference and for important team gatherings. Daily collaboration follows classic agile rituals including daily standups and Scrum sprints, with high trust and autonomy placed in individual contributors.

• High autonomy and trust within a low-hierarchy, pragmatic engineering culture.
• True flexible working setup with no rigid office mandates and Berlin hub access.
• Direct cross-functional influence across multiple active product squads.
• Collaborative agile sprint rituals with minimal bureaucracy and fast decision-making.

Python · Apache Airflow · SQL · DBT · Google BigQuery · Snowflake · AWS · GCP · Looker · LookML · Go · CI/CD

This probably isn't for you if:

• You prefer working in siloed infrastructure teams without direct interaction with product managers and analysts.
• You require rigid top-down roadmaps and step-by-step guidance rather than self-directed problem solving.
• You want to focus purely on backend scripts without touching analytics modeling tools like DBT or Looker.

If you are ready to drive our data platform forward and build impactful infrastructure across our product squads, let's talk. Apply today to connect with our Engineering Lead.