Senior AI & Data Tooling Engineer/Data Steward (f/m/x)

INNOVATION IS IMAGINING WHAT NO ONE ELSE CAN. 

 

At the BMW Group, everything begins with passion. It transforms a profession into a vocation. It drives us to continually reinvent mobility and bring innovative ideas to the roads. Enthusiasm for collaborative projects turns a team into a strong unit where every opinion is valued. It is only when expertise, highly professional processes, and enjoyment of work come together that we can shape the future collectively.

 

As a Senior AI & Data Tooling Engineer with a focus on Data Stewardship, you ensure that data is provided in standardised formats, continuously maintained, and supported by a robust technical tooling landscape – with the ultimate goal of enabling cross-domain and cross-generation AI use cases.

What awaits you?

• You define and implement standards for data formats, interfaces, and semantic models to create an interoperable data foundation for enterprise-wide AI applications.
• You develop and operate technical solutions for data harmonisation and transformation, including the implementation of standards and automated mapping processes.
• You ensure that data from diverse sources is automatically converted into unified, reusable formats, including validation, versioning, and metadata management.
• You implement continuous data management, monitoring data quality, managing retention and deletion policies, and optimising data inventories.
• You take ownership of Data Request Management by identifying missing data, coordinating requirements, and implementing technical integration – such as connecting new data sources, API integration, ETL pipelines, and automating data flows.
• You integrate these processes into existing MLOps and DevOps toolchains, automating workflows for data provisioning and governance.
• You evaluate emerging technologies (e.g., semantic layers, data catalogues, generative AI tooling) and actively contribute to the evolution of our data strategy.

What should you bring along?

• A university degree in Computer Science, Data Science, or a comparable qualification.
• At least five years of professional experience in data management, AI platform engineering, or tooling.
• A deep understanding of data formats and interfaces (e.g., JSON, MCAP, Avro, API design, semantic models).
• Hands-on experience in the technical implementation of data harmonisation and container-based formats.
• Solid knowledge of cloud architectures (mainly AWS) and container orchestration (Docker, Kubernetes).
• Strong programming skills in Python and scripting for automation.
• Very good written and spoken English skills. Knowledge of German, both written and spoken, is an advantage.

Would you like to help us drive the AI transformation at BMW? Apply now!

Find out more about Artificial Intelligence at the BMW Group here.

Note: Please apply exclusively online via our career portal. Applications via other channels (especially e-mail) cannot be considered.

What we offer?

• Challenging projects in which we shape the mobility of tomorrow together.
• A wide range of personal and professional development opportunities.
• Attractive, fair, and performance-related remuneration.
• A high level of job security.
• Annual special payments such as holiday pay, Christmas bonus, and profit sharing.
• Flexible working hours including six weeks’ annual leave and overtime compensation.
• Discounted BMW & MINI conditions.
• Many other benefits at bmw.jobs/benefits

Start date: From now on
Type of employment: Unlimited
Working hours: Full-time

When you apply, the next steps in the selection process include an online test followed by interviews with the hiring manager (either virtual or in person).

Do you have any questions? Then simply send your enquiry using our contact form. Your enquiry will then be answered by telephone or e-mail.

At the BMW Group, we place great importance on equal treatment and equal opportunities. Our recruitment decisions are based on the personality, experience, and skills of the applicants. Learn more here.