Senior MLOps/Data Engineer
Summary
Senior MLOps/Data Engineer at TomTom owning the end-to-end ML lifecycle on Azure and Databricks: orchestrating ML pipelines, standardizing experimentation with MLflow, automating via CI/CD, and building data/model observability for production models. Requires 3+ years in Data Eng/MLOps with strong Python, PySpark, and Databricks/Delta Lake skills.
In this role you own the end-to-end ML lifecycle on Azure and Databricks, collaborating with applied scientists to operate reliable models. You will orchestrate ML pipelines and standardize experimentation, leveraging MLflow and CI/CD tooling. You’ll implement data and model observability, ensure security and compliance, and manage incidents and post-mortems to keep pipelines running smoothly. This is a hands-on, production-focused ML/MLOps position with a scale-oriented, governance-minded team.
Verantwoordelijkheden- Own the end-to-end ML lifecycle on Azure and Databricks
- Orchestrate and maintain ML pipelines (ingest, feature engineering, train, evaluate, deploy, monitor, repeat)
- Standardize experimentation using MLflow or similar (tracking, artifacts, model registry, stages)
- Automate jobs with Databricks Workflows and CI/CD (GitHub Actions or Azure DevOps)
- Implement data and model observability (freshness, drift, SLA/SLO monitoring)
- Ensure security & compliance
- Handle incidents and post-mortems for ML pipelines and serving infrastructure
- 3+ years in Data Eng/MLOps roles
- Excellence in Python software engineering and developing tests
- Fundamental understanding of Machine Learning
- Strong PySpark
- Hands-on with Databricks and Delta Lake
- CI/CD for data/ML (Git, PR workflow, automated tests, environment pinning)
- Azure basics
- Monitoring and building dashboards
- Clear communication; operational-excellence mindset (SLA/SLO ownership)
- clear communication
- ownership mindset
- Python
- PySpark
- Databricks
- Delta Lake