Key Responsibilities:
As Technical Lead – Data & Analytics, you will define and drive the technical vision behind VEACT's data platform, powering the analytics, AI, and data engineering capabilities that transform raw automotive data into measurable business value. Your technical leadership will elevate data quality, pipeline reliability, and model performance across the entire VEACT Mobility Suite, enabling OEMs and dealer networks to make smarter, faster decisions.
- Define and own the technical architecture, standards and best practices for VEACT's data platform, including data pipelines, Lakehouse infrastructure and analytical models
- Lead technical decision-making across the Data & Analytics Squad, guiding data engineers, analysts and ML engineers on design, implementation and code quality
- Design and evolve scalable, reliable data pipelines using technologies such as Flink, Iceberg, dbt, AWS Athena, Postgres and Argo workflows
- Drive data quality frameworks and observability to ensure accuracy, consistency and reliability of analytical outputs
- Mentor and grow the technical capabilities of squad members through code reviews, pair programming and knowledge sharing
- Partner closely with the Product Manager – Data & Analytics to translate product requirements into robust technical solutions
- Evaluate and introduce new technologies, tools and approaches that strengthen VEACT's data and ML capabilities
- Build an inclusive and psychologically safe team environment, in which team members feel supported and heard
Who you are and what you bring:
- Fluent in English (C1) and German (C1) is a plus
- 5+ years of hands-on experience in data engineering, analytics engineering or a related technical role
- Deep proficiency with modern data stack: SQL, dbt, Python, Lakehouse/data warehouse architectures (e.g., Iceberg, AWS Athena, Postgres, Flink)
- Strong understanding of data modeling, ETL/ELT patterns, data quality frameworks and pipeline orchestration (e.g. Argo workflow)
- Experience leading or mentoring technical teams, with a track record of improving engineering practices and code quality
- Solid understanding of ML/AI pipelines and statistical methods
- Excellent communication skills: able to bridge technical complexity with business context and collaborate effectively across disciplines