Lead Data Engineer

Lead Data Engineer

FORVIA HELLA is a listed international automotive supplier. As a company of the FORVIA Group, FORVIA HELLA stands for high-performance lighting technology and vehicle electronics and, with the Lifecycle Solutions Business Group, also covers a broad service and product portfolio for the spare parts and workshop business as well as for manufacturers of special vehicles. With currently around 36,500 employees at over 125 locations, the Company is active worldwide and generated adjusted sales of €8.1 billion in fiscal year 2024.

YOUR TASKS
We’re hiring a Lead Data Engineer to join our Data Engineering team as a high-impact individual contributor. This team powers the data exchange between Hella Gutmann’s sourcing systems and data-driven products and services. Your work will directly influence the scalability of our digital portfolio and have a measurable impact on company revenue. What You’ll Do Architect and optimize our cloud-native data platform on AWS, ensuring high performance, reliability, and scalability. Build and maintain robust data pipelines to ingest, transform, and store data in centralized cloud repositories. Develop and manage integration tools, databases, and data access layers in an agile product environment. Ensure data is quality-assured, discoverable, and accessible for internal applications and services. Deliver analytics solutions to internal stakeholders, enabling data-informed decisions. Work independently while collaborating closely with cross-functional teams — this is a hands-on role, not a managerial one. YOUR QUALIFICATIONS
What We’re Looking For 10–12 years of experience in data engineering, including ETL, data modeling, and working with both relational (MySQL) and document-oriented (DynamoDB) databases. Deep expertise in the AWS ecosystem, including Lambda, EC2, ECS, EKS with Spark, S3, Athena, CloudWatch, OpenSearch, API Gateway, Cognito, SQS, and Terraform. AWS certification (e.g., Solutions Architect – Professional or Data Analytics – Specialty) or proven hands-on experience with complex AWS deployments. Excellent programming skills in Python. Hands-on experience with Apache Airflow for orchestration. Familiarity with monitoring and observability tools such as CloudWatch, Prometheus, or Grafana, along with a solid grasp of SRE best practices including automated testing, CI/CD, infrastructure as code, and SLOs. Strong product thinking and the ability to translate business needs into scalable data solutions. A proactive mindset with a strong sense of ownership and eagerness to learn.

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