Data Product Owner (m/f/d)
First seen by Alion on Oct 15, 2026.
About autoSense
autoSense AG is a fast-growing corporate start-up of the AMAG Group and Zurich Insurance, focused on charging solutions for electric vehicles. Our team brings together more than 10 nationalities and works with flat hierarchies on one of the central questions of the mobility transition: how employees and fleets can charge simply, predictably, and fairly - at home and on the road.
What we offer
- Flexible working and home-office options
- Central office in Zurichs Kreis 4 with access to the roof terrace
- A wide variety of lunch options nearby
- Fair compensation and further benefits
- The chance to shape the data foundation of a growing corporate start-up - with short decision paths and a direct line to management
Requirements
- 3+ years in data roles, including at least 1-2 years with product or product-owner responsibility
- A solid understanding of how a modern data platform fits together: ingestion, transformation, orchestration, and presentation
- Hands-on experience with our stack or similar tools: Snowflake, dbt, Airflow, Airbyte, Python
- Strong SQL. You can read a data model and question it.
- Comfort translating between business and engineering, and the confidence to say no
- Fluent English and comfortable with German
Responsibilities
- Shape how autoSense builds and uses data, and set priorities for the data team
- Turn business and partner needs into data products
- Own the data teams backlog: prioritise, refine, and run sprint planning
- Work with internal stakeholders (sales, operations, finance, management) to shape requirements into clear, deliverable data products
- Lead and coordinate the work of internal and external data engineers and developers, keeping priorities aligned and delivery on track
- Own customer-facing data products for partners and customers, such as dashboards, reporting, and APIs
- Drive a unified approach to data: set standards and define data models together with engineering and the business
- Stay close to the code: review pull requests, prototype in SQL, and help debug issues across the pipeline