MLOps Engineer (Azure & Databricks)

Data by Example delivers IT solutions focusing on meaningful data processing. The current project involves rebuilding internal machine learning software for forecasting thousands of time series during each processing cycle for a client in the HVAC industry. The objective is to create a production-grade solution with high standards of maintainability, flexibility, scalability, and operational excellence.

• Minimum 5 years of commercial experience in a similar position
• Expert knowledge and experience with the Databricks platform (Unity Catalog, workspaces, clusters, jobs, Databricks Asset Bundles/declarative deployments, environment separation: dev, qa, prod)
• Advanced programming skills in Python including concurrency and parallel task processing within Databricks, especially using Spark
• Automation of CI/CD processes using GitHub Actions, including build, test, deploy, and release gates
• Optimization of performance and costs in Spark/Databricks environments through cluster tuning, parallel processing, and task runtime profiling
• Implementation of monitoring and observability mechanisms (logs, metrics, alerts, dashboards, runbooks, data quality monitoring)
• Release management, versioning, deployment oversight, and rollback strategies
• Practical use of AI-assisted development tools to improve engineering efficiency
• Working experience with MLflow at intermediate level, including experiment tracking, model registry, and lifecycle management

• Build solid engineering foundations
• Automate scalability and observability
• Implement release processes and ML model lifecycle management in Databricks to ensure reliable and cost-efficient deployment and operation of data and ML tasks

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