About the Company (Remote Europe)

Our client is a Berlin-based, remote-first technology company building advanced market intelligence and software solutions for the automotive industry.

With an established product and a strong technical team, the company operates in a stable growth phase, continuously improving its data platform to deliver highly reliable insights to customers.
This isn't a typical ETL maintenance role. You'll help design and evolve the platform that powers millions of vehicle records, building reliable data pipelines, improving data quality, and solving complex data standardization challenges.

If you enjoy designing scalable data systems, owning production pipelines, and working with modern cloud technologies, we'd love to hear from you.

What you'll do

• Design, build, and maintain scalable batch and streaming data pipelines.

• Develop reliable ETL/ELT workflows using Python, Spark, and modern orchestration tools.

• Improve data quality, validation, monitoring, and observability across the platform.

• Design data models that support analytics and product development.

• Build ingestion pipelines connecting multiple external and internal data sources.

• Optimize large-scale processing performance and platform reliability.

• Work closely with product managers and engineers to translate business requirements into technical solutions.

• Use modern AI-assisted development tools to improve engineering productivity.

We're looking for someone who has

• 4+ years of experience as a Data Engineer.

• Strong Python and SQL skills.

• Hands-on experience with Spark/PySpark.

• Experience building production ETL/ELT pipelines.

• Strong understanding of data modeling principles.

• Experience with workflow orchestration tools such as Airflow.

• Experience working with cloud data platforms.

• A strong ownership mindset and the ability to work independently.

• Professional English.

Nice to have

• Delta Lake or Lakehouse architecture.

• MongoDB or other NoSQL databases.

• CDC and streaming technologies (Kafka, Debezium, etc.).

• Data quality frameworks (Great Expectations or similar).

• Experience with metadata, lineage, or observability tools.

• Familiarity with AI-assisted development (GitHub Copilot, Cursor, Claude Code, etc.).

Why join

• Build a modern data platform from the ground up rather than maintaining legacy systems.

• Work on technically challenging problems involving large-scale data integration and quality.

• Join a highly collaborative engineering team where you'll have real ownership and influence over technical decisions.

• Fully remote position within Europe.

• Long-term product with significant technical challenges and room for growth.