Senior Data Engineer, Compute

About Bolt Bolt is shaping a future where cities are built for people, not cars. What started as an ambitious project of a 19-year-old in 2013 has grown into a global mobility platform used by more than 200 million customers and 4.5 million driver and courier partners across 50 countries.

From ride-hailing and food delivery to scooters, e-bikes, and car-sharing, Bolt helps people move through cities every day. Small, autonomous teams drive this work, combining the speed and ownership of a startup with the scale of a global technology company backed by more than €1bn in funding.

And we're just getting started.

Why join Bolt?

• Build the future of mobility and help transform how people live and move in cities.
• Tackle challenges at scale that span technology, operations, regulation, and growth.
• Take real ownership early. Small, lean teams mean your decisions matter from day one, and you'll learn fast alongside some of the best people in the industry.
• Join one of Europe's leading technology companies, backed by world-class investors including Sequoia.

About The Role Data Platform Compute builds and runs the compute layer that every data practitioner at Bolt depends on. If someone at Bolt schedules a pipeline, opens a notebook, trains a model, or runs an experiment, they are running on infrastructure we own.

We operate platform-as-a-product: our customers are internal, our measure of success is developer productivity and time-to-insight across the data organisation, and the best outcome is teams shipping at speed without ever needing to talk to us.

Main Tasks And Responsibilities

• Design, build, and operate self-serve solutions based on Databricks, Airflow, and Spark infrastructure that runs Bolt's data workloads so that data practitioners can provision, deploy, and debug.
• Keep 800+ daily Databricks jobs reliable, observable, and cost-efficient with an observability layer that detects pipeline failures and surfaces areas for improvement.
• Scale Looker reporting and ad-hoc querying on shared warehouses; own routing, cluster sizing, and the performance-versus-cost trade-offs for the 4,000+ Bolt employees, serving 300,000+ queries daily over petabytes of data.
• Build the AI surface over the platform - stand up Databricks MCP servers, put agents to work on our pipelines, and build the self-service tooling that means teams no longer route through us.
• Work directly with Analytics Engineering, Data Science, ML, Experimentation, Ingestion, Governance, and SRE Data teams - as a partner.

About You

• At least 5 years of software engineering experience, including hands-on experience with large-scale distributed data systems or compute engines like Apache Spark.
• Proficient in Python or another mainstream OOP language. We care about strong engineering fundamentals and adaptability.
• Familiar with the modern data stack (dbt, Databricks, Airflow, or equivalents)
• Hands-on with Databricks in production, especially Unity Catalog, cluster policies, or serverless compute and performing cloud cost optimisation at scale.
• Solid AWS fundamentals (IAM, S3, EC2, networking) and infrastructure as code, ideally Terraform.
• You treat CI/CD, testing, and observability as core engineering principles, not afterthoughts.

Some perks may differ depending on your location and role. At Bolt, using AI daily is a baseline expectation for everyone. If there's a faster, smarter way to do your work, we expect you to find it. You're still responsible for the output, so the standard stays high when using AI tools. Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don't tick every box, please consider applying!

Everyone is welcome

Bolt is an equal opportunity employer. We are committed to building a diverse and inclusive workplace where all qualified applicants are considered for employment without regard to race, colour, nationality, religion, gender or gender identity, sexual orientation, age, or disability.

We welcome applications from all backgrounds and are happy to make reasonable accommodations throughout our hiring process. If you require any adjustments, please let us know.