Senior Data Engineer (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 products and data foundation of a growing corporate start-up - with short decision paths and a direct line to management
Requirements
- 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 dont 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
Responsibilities
- 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 the pipeline
- Keep it reliable: monitoring, data quality tests, incident handling, and an eye on Snowflake and AWS costs
- Lead the delivery: coordinate the work of our internal and external data engineers while building alongside them
- Understand the problem: work with sales, operations, finance, management and partners 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
- 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
- Look after data security: apply access control, data protection and the relevant ISO 27001 controls within the data platform, and support our annual audits