Platform Engineer Data & ML

Are you a platform engineer ready to scale your impact, work with cutting-edge tech, and see your work directly drive real-world financial decisions? At Bridgefund we are looking for a Platform Engineer Data & ML to help build and optimize the platform powering our automated lending.

As a Platform Engineer - Data & ML, you are the technical architect behind the liberation of money. By building a high-performance data platform, you directly enable BridgeFund's mission to move capital out of stagnant banks and onto the "work floor". You bridge the gap between complex data and real-world impact, designing the automated systems that allow entrepreneurs to skip the "human bottlenecks" and get a decision in record time.

To fulfill this vision, your goal is to turn messy data into a standardized, production-grade ecosystem. By architecting a platform that powers 200+ production workflows and 30+ ingestion pipelines through medallion layers on Databricks, you ensure our financing remains simple, fast, and fair. Your focus on MLOps foundations and data contracts provides the reliability needed to scale our impact. Ultimately, you aren't just managing infrastructure; you are building the bridge that gives entrepreneurs their autonomy back.

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  Build the MLOps Platform that powers credit risk scoring, automated lending decisions, and transaction categorisation. This platform supports the full ML lifecycle from feature engineering to production inference.

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  Drive performance and cost optimisations for heavily computational Spark jobs and improve scalability of the data & ML platform.

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  Drive adoption of platform standards like ingestion frameworks, data modelling conventions, data contracts, and ML operations patterns (feature stores, model registry, reusable training/inference pipelines).

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  Architect CI/CD infrastructure, shared tooling, and multi-environment deployment strategies across a growing multi-repo ecosystem

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  Strengthen data governance, access controls, security practices, and SDLC maturity. Support data science teams in adopting these standards

• 5+ years of experience as a Data Engineer, Platform Engineer or ML Engineer

• Bachelor's or Master's degree in Computer Science, Engineering or another technical field

• Strong experience with Python and/or PySpark, and solid SQL skills

• Familiarity with Databricks and Databricks Asset Bundles (DABs)

• Experience with orchestration tools like Databricks Lakeflow Jobs, Airflow or Dagster

• Experience building and maintaining CI/CD pipelines

• Hands-on experience with unit and integration testing

• Understanding of containerisation techniques such as Docker

• Familiarity with data architecture and system design

• A collaborative mindset and the ability to explain technical concepts clearly

• A practical problem-solver who enjoys collaborative engineering and understands that the true value of a data product is realized in production, one release at a time.

While small businesses drive the economy, when it comes to financing, traditional systems still move at the speed of paper. We founded BridgeFund in 2018 to change that. We've stripped away the bureaucracy: an entrepreneur applies in just five minutes, and our advanced technology processes the data quickly and efficiently. By combining cutting-edge automation with real human logic, we make financing decisions that are both fast and fair. We grew 75% last year and have proudly fast-tracked over €700 million in loans to entrepreneurs. Our next goal? To scale our data capabilities by making our platform even sharper, ensuring support for the next generation of entrepreneurs

Good. That is usually how the best engineers start here at BridgeFund. Apply directly or reach out to Anna-Maria at recruitment@bridgefund.nl. We would love to hear what you would build next.