Senior Data Engineer AWS & Databricks

The project:

We’re looking for a Senior Data Engineer to join a team supporting our client — a leading player in the automotive industry, currently driving a large-scale initiative to build a unified data platform that will shape how connected vehicle data is used across Europe. The goal is to create a modern, scalable platform (built on Databricks on AWS) that consolidates client's vehicle data from multiple sources into one ecosystem, enabling analytics, AI/ML innovation, and data-driven decision-making. You’ll be part of an international team working with data mesh and lakehouse principles, helping design, develop, and maintain a platform that ensures data quality, security, and interoperability — while unlocking new business value for the client’s connected vehicle services.

📌 In the role of Data Engineer you will:

• Design, build, and maintain robust data ingestion pipelines from multiple vehicle data sources.
• Develop and optimize data transformation workflows and orchestration logic using modern data tools.
• Design and implement complex ETL/ELT processes, ensuring high data quality and performance.
• Troubleshoot and resolve pipeline failures and performance bottlenecks.
• Ensure data integrity, consistency, and accuracy across all stages of the data lifecycle.
• Collaborate with business and IT teams to define and deliver data requirements and specifications.
• Prepare and maintain detailed documentation of data sources, ingestion logic, and transformation processes.
• Regularly monitor and report on data quality and platform performance.
• Mentor and support other team members, contributing to best practices and a data-driven culture.

Requirements:

• 5+ years of hands-on experience in data engineering using Python and SQL.
• Strong experience working with AWS and data warehousing services (e.g. Redshift, Databricks, or similar).
• Expertise in ETL/ELT and data orchestration frameworks (e.g. PySpark, Airflow, AWS Glue).
• Experience with real-time or stream processing (e.g. Kafka, Flink, or Spark Structured Streaming).
• Solid understanding of data lake and data warehouse architecture and best practices.
• Skilled in Git and familiar with CI/CD pipelines for data projects.
• Strong background in data analysis and familiarity with tools like Power BI.
• Proven ability to gather, document, and translate business requirements into technical solutions.
• Collaborative mindset, attention to detail, and a passion for building scalable, high-quality data systems.

Benefits:

• Life insurance
• Multisport card
• Fully remote job
• Private medical care
• Flexible working hours
• B2B contract
• Amazing integration events on a regular basis
• Training budget
• Opportunity to impact our company culture build-up
• Work equipment (laptop, 2 monitors, and accessories)

Interview process:

• Initial interview with Paulina, our recruiter - 30 minutes
• Technical interview with one of our technical interviewers - 30-45 minutes
• Interview with the client - 1 hour