The role
As Senior Data Engineer / Data Product Owner, you own autoSense's data products and the platform behind them, through our ETL/ELT pipelines, from stakeholder conversations and backlog refinement to hands-on development on our stack (AWS, Airflow, dbt, Snowflake, Tableau). The platformis already in place. Your job is to run it reliably, improve it, and build on it, hands-on together with the team.
You talk to sales, operations, finance, management and our partners, work out what they actually need, and turn that into a clear backlog. Then you lead the delivery and take an active part in building it. You are also accountable for data security across the data platform, making sure our charging, vehicle and customer data is protected, governed and audit-ready.
What you'll do
Build and run the platform
• Own the pipelines: operate and evolve our ETL/ELT stack on AWS: Airbyte for ingestion, Airflow for orchestration, dbt for transformation and Snowflake as the warehouse
• Model the data: design dbt models and Snowflake schemas that the business can rely on and understand
• Write production code: develop in SQL and Python, review pull requests, and debug issues across thepipeline
• Keep itreliable: monitoring, data quality tests, incident handling, and an eye onSnowflake and AWS costs
• Lead the delivery: coordinate the work of our internal and external data engineers while building alongside them
Turn needs into data products
• Understand the problem: work with sales, operations, finance, management andpartners to find the real question behind a request
• Shape the backlog: translate requirements into clear user stories, help prioritise, and make trade-offs visible
• Deliver data products: build internal and customer-facing products such as data sources for dashboards, reports, exports and APIs
Set standards and work across teams
• Drive consistency: establish shared definitions, data models, documentation and engineering practices
• Work with Engineering: align with our backend developers (Node.js, TypeScript, PostgreSQL) on source schemas, events and data contracts
• Lookafter data security: apply access control, data protection and the relevant ISO27001 controls within the data platform, and support our annual audits
What you bring
• 4+ years in data engineering or a closely related role
• Hands-on production experience with Snowflake, dbt and Airflow (or comparable tools) on AWS. You build it yourself, you don't just specify it
• Strong SQL and good Python skills
• Experience working directly with business stakeholders: you ask the right questions and explain technical trade-offs in plain language
• A good grasp of data security and data protection in practice (e.g. access control,revFADP/GDPR)
• Fluent English; German is a strong advantage
Nice to have
• Product owner or comparable product responsibility, e.g. owning a backlog or a data product end to end
• Experience with ISO 27001 or similar security frameworks
• Experience with Tableau or a comparable BI tool, ideally for internal and external users
• Ability to read and contribute to Node.js / TypeScript code
• Experience with AI/ML or generative AI, e.g. building LLM-based features with AWS Bedrock
• Experience in e-mobility, energy or mobility services
• Experience building data products or APIs for external customers or partners
About autoSense
autoSenseAG 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 Zurich's 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 products and data foundation of a growing corporate start-up – with short decision paths and a direct line to management
