Data Engineer

We exist to unleash the power of the self-employed - helping solopreneurs and micro-businesses thrive by doing what they're passionate about and removing the complexity of building lasting, successful businesses.

Jimdo started in 2007 when three school friends built a website builder in a Northern German farmhouse to help everyone build a presence online. Today, we're a profitable, remote-first company with 220+ people from 50+ nationalities working across 15+ countries. We've helped build over 36 million websites to get online across the world.

We're more than just a website builder. We're an AI-powered platform that helps self-employed people actually run and build successful businesses — from getting found online, winning customers and running their business with a peace of mind by knowing exactly what to do next to move forward.

At the heart of Jimdo is a strong belief in personalized, data-driven guidance. Our platform combines design, business tools, and an AI-powered core that turns real customer data into clear insights and next steps helping our customers focus on what moves their business forward.

As a Data Engineer, you'll be a hands-on contributor within our Data Platform team, building and maintaining the pipelines, models, and integrations that drive data-informed decision-making across Jimdo. Reporting to the Data Platform Manager, you'll own well-defined projects end-to-end—from implementation and testing through monitoring and optimization—while collaborating closely with senior engineers, analysts, and stakeholders.

This role offers the opportunity to work with a modern cloud data stack including Snowflake, dbt, Airflow, AWS, and AI-powered engineering tools.

• Build and maintain scalable data pipelines, transformations, and reporting models using dbt, SQL, Python, and Snowflake.

• Develop and optimize data ingestion workflows, API integrations, and CDC pipelines using established engineering frameworks and best practices.

• Implement data quality checks, testing, monitoring, and observability mechanisms to ensure reliable and trustworthy data products.

• Design and maintain analytics-ready data models, including reporting marts and dimensional models that support business insights.

• Leverage AI-powered development tools such as GitHub Copilot and Claude to improve productivity, code quality, and documentation.

• Collaborate with analysts, BI teams, and stakeholders to define metrics, clarify business logic, and deliver impactful data solutions.

• Contribute to data governance, compliance, and platform reliability by following data contracts, security standards, and engineering best practices.

• 4+ years of experience in Data Engineering, Analytics Engineering, or a related field.

• Strong SQL skills, including complex joins, aggregations, CTEs, and window functions.

• Hands-on experience with dbt for data transformation, testing, and documentation.

• Practical experience with cloud data warehouses, preferably Snowflake.

• Experience building data workflows and automation using Python.

• Familiarity with orchestration tools such as Airflow and Git-based development workflows.

• Strong problem-solving skills, attention to detail, and a collaborative mindset.

• Experience with AWS services.

• Exposure to data governance, data contracts, and compliance frameworks.

• Experience using AI coding assistants and integrating AI into engineering workflows.

• Familiarity with modern observability and monitoring practices for data platforms.