Software Engineer III (Data Engineering)

The Road Features Group, part of ADAS & ADS at TomTom, is the algorithmic engine behind the creation of highly accurate HD maps that enable lane-level navigation and autonomous driving. We build digital twins of road networks faster and more accurately than ever before. Using diverse data sources — including on-vehicle, aerial, and street-side sensors producing semantic 3D data — we extract road surfaces, drivable lanes, traffic behaviors, and physical structures.

Within this group, the Road Surface Graph (RSG) & Lanes team plays a pivotal role: turning massive-scale sensor and geospatial data into detailed drivable road and lane graphs. Our work blends computational geometry, classical computer vision, and large-scale data engineering to push the boundaries of mapmaking technology. Join us in setting new standards for mapping technology and making road feature extraction smarter and more efficient.

We are seeking a mid-senior Data Engineer to directly support the Applied Science (AS) team in building robust ML data pipelines, validation frameworks, and testing infrastructure for computer vision and mapping algorithms. You will work closely with applied scientists to prepare datasets, train models, and validate algorithms. You will build systems that rapidly train, measure and evaluate algorithmic libraries, ensuring they will run reliably at scale when released to production.

This is a hands-on engineering role where data preparation, quality control, pipeline development, and operationalization are central. You will also gain exposure to machine learning, deep learning and geometric computer vision systems in production.

What you'll do:

• Develop and maintain the data lifecycle critical for the training and development of algorithms.
• Build an algorithm and model registry for the tracking and versioning of algorithmic libraries.
• Enable rapid and reliable regression testing of algorithms on city-scale datasets
• In coordination with Engineering teams, ensure a full release process and algorithm integration into production pipelines.
• Develop automated integration tests, validation suites, and quality metrics for algorithm outputs.
• Implement observability and monitoring for pipelines and algorithm outputs, including dashboards (e.g., Grafana) and metrics tracking.
• Support algorithm development by preparing and manipulating large-scale datasets.
• Assist data- and applied scientists in integrating, updating, and maintaining code in large repositories to ensure compatibility and smooth deployment.
• Deploy algorithms on Azure/Databricks using Docker and CI/CD pipelines for reliable delivery.
• Collaborate with map production and operational teams to triage issues, prioritize fixes, and ensure production reliability.

What you'll need:

• MSc. in Computer Science, Software Engineering, or related field.
• 4–6 years of professional software engineering or data engineering experience, ideally with large-scale data systems.
• Strong Python skills and hands-on experience with Scala, PySpark/Spark; pandas for local development.
• Proven track record building reliable pipelines and data-quality frameworks; experience with pytest, Git, and CI/CD (Azure DevOps/GitHub Actions).
• Strong knowledge of cloud platforms (Azure, Databricks) and containerization (Docker).
• Ability to think end-to-end and deliver robust, production-ready solutions.
• Strong problem-solving skills and ability to work collaboratively with scientists and engineers.

Nice to have:

• Familiarity with other programming languages (Java, C++).
• Experience with observability, metrics collection, and dashboards (Grafana, logging, monitoring).
• Experience with geospatial frameworks/libraries (GeoPandas, Shapely, Spark geospatial libraries).
• Knowledge of metadata/lineage systems (Unity Catalog, Purview) and dataset / model versioning (MLflow).

What we offer

• A competitive compensation package, of course.
• Time and resources to grow and develop, including a personal development budget and paid leave for learning days, as well as paid access to e-learning resources such as O’Reilly and LinkedIn Learning.
• Time to support life outside of work, with enhanced parental leave plus paid leave to care for loved ones and volunteer in local communities.
• Work flexibility, where TomTom’ers, in agreement with their manager and team, use both the office and home to focus, collaborate, learn and socialize. It’s all about getting the best out of both worlds – we ask TomTom’ers to come to the office two days a week, and the remaining three are free to be worked in either location.
• Improve your home office with a setup budget and get extra support with a monthly allowance.
• Enjoy options to work from your home country and abroad for a set number of days each year, to visit family and friends, or to simply explore the world we’re mapping.
• Take the holidays you want with a competitive holiday plan, plus an extra day off to celebrate your birthday.
• Join annual events like our Hackathon and DevDays to bring your ideas to life with talented teammates from around the world.
• Become a part of our inclusive global culture and have the chance to collaborate with a diverse community – we have over 80 nationalities at TomTom!

Meet your team

We are the ADAS & ADS Product Unit, leading the production of TomTom’s HD maps and ADAS technology. In a diverse team of applied scientists, engineers, data scientists, and more, equipped with a broad array of expertise, you’ll collaborate on groundbreaking location-based technologies and applications. More specifically, you’ll be at the forefront of the creation of advanced HD maps. You’ll also help update these in real-time, ensuring our maps are pushing the world forward instantly. These maps will then go on to empower the largest car manufacturers, transportation giants, and major tech companies around the world.