About this role
Senior MLOps/Data Engineer Amsterdam, The Netherlands What you'll do In a nutshell, own the end-to-end ML lifecycle on Azure and Databricks, working with applied scientists to operate reliable models. - Orchestrate and maintain ML pipelines (ingest → feature engineering → train → evaluate → deploy→monitor→repeat) on Azure + Databricks - Standardize experimentation using MLflow or similar tools (tracking, artifacts, model registry, stages) - Automate jobs with Databricks Workflows and CI/CD (GitHub Actions or Azure DevOps) - Implement data & model observability: freshness/completeness, drift (features/model), training/serving skew, SLA/SLO monitoring - Ensure security & compliance - Handle incidents and post-mortems for ML pipelines and serving infrastructure What you'll need - Excellence in Python software engineering and developing tests - Fundamental understanding of Machine Learning - 3+ years in Data Eng/MLOps roles - 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) What's nice to have - Unity Catalog experience - Databricks Feature Store - Terraform for workspace/clusters/jobs/UC objects - Telemetry domain exposure - Optimize PySpark jobs (partitioning, caching, etc.) and cost (autoscaling, spot). 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. Improve your home office with a setup budget and get extra support with a monthly allowance. Take the ho...