Data engineer in automotive

We’re looking for a Data Engineer Specialist who combines deep technical expertise with a genuine passion for people, leadership, and building exceptional products. In this hands-on leadership role, you’ll have the opportunity to lead and grow a team of data engineers while staying close to the technology. You’ll influence architecture, engineering standards, and delivery practices, and help build reliable, scalable data products that solve meaningful challenges.

• Lead, mentor, and empower a team of data engineers, providing technical direction, guiding architecture decisions, and creating an environment where people can grow and do their best work.
• Take ownership of scalable data solutions from design and implementation through deployment, monitoring, optimization, and production support.
• Design, build, and optimize robust ETL/ELT pipelines across staging, warehouse, and data mart layers.
• Use advanced SQL to create high-performing transformations and define effective partitioning and clustering strategies.
• Shape warehouse architecture and schema design, including dimensional modelling and slowly changing dimension (SCD) patterns.
• Build Python connectors, orchestration scripts, reusable services, and data contract validation logic.
• Develop reliable event-driven and streaming solutions with Apache Kafka, with a strong focus on version-controlled, testable transformations and built-in assertions.
• Embed automated data quality and contract testing into the engineering lifecycle so issues are identified early and releases remain dependable.
• Build secure, scalable, and cost-efficient solutions on Google Cloud Platform (GCP), continuously balancing performance, reliability, and cloud spend.
• Use Cloud Composer / Apache Airflow to orchestrate workflows, schedules, and dependencies across the data ecosystem.
• Automate cloud infrastructure with Terraform or similar Infrastructure as Code (IaC) tooling, covering areas such as storage, datasets, IAM, and networking.
• Strengthen engineering practices through Git-based CI/CD, code reviews, automated testing, and controlled deployments using tools such as Cloud Build or GitHub Actions.
• Help shape standards for code quality, testing, documentation, observability, security, reliability, and data governance.
• Collaborate with architects, product teams, analysts, data scientists, and engineers to turn complex requirements into maintainable data products with tangible impact.

• Significant hands-on experience in Data Engineering, designing and delivering production-grade data platforms and pipelines.
• Experience leading, mentoring, or technically guiding engineers while remaining actively involved in architecture and development.
• Strong SQL expertise, including complex transformations, query optimization, partitioning, and clustering across staging, warehouse, and data mart layers.
• Solid knowledge of data warehousing, dimensional modelling, schema design, and slowly changing dimensions (SCD).
• Strong hands-on Python skills for connector development, data processing, automation, orchestration, and validation frameworks.
• Practical experience building cloud-native data solutions on GCP, with an understanding of performance and cost optimization.
• Hands-on experience with Apache Kafka and event-driven or streaming architectures.
• Experience building automated data quality, contract-validation, and transformation tests as part of version-controlled engineering workflows.

• A fast-paced tech environment
• Continuous growth & learning
• Open feedback culture
• Room for own initiative & ideas
• Transparency about results & strategy
• Recognition & reward for hard work
• Working with a flexible schedule
• Medical subscription
• Meal tickets
• Extra vacation days - starting with 25 vacation days
• Many others perks