We are looking for an experienced ML Engineer with strong expertise in Databricks, Unity Catalog, Feature Store, Python, Spark, and Azure to build and maintain data and machine learning workflows for production environments.
馃敼 Key Responsibilities
- Set up and manage Unity Catalog in Databricks for data organization, governance, and access control.
- Design and operationalize Feature Stores to support ML models in production.
- Build scalable ETL/ELT pipelines using Databricks, Python, and Spark.
- Integrate Databricks with Azure Cosmos DB, ACR, AKS, and other Azure services.
- Monitor and optimize pipeline and Feature Store performance.
- Support reliable and scalable ML workflows in production.
馃敼 Required Skills
- Strong hands-on experience with Databricks Unity Catalog.
- Experience with Databricks Feature Store or similar solutions.
- Strong Python, Spark/PySpark, and data engineering skills.
- Proficiency in Java.
- Experience with Azure Cosmos DB, ACR, and AKS.
- Knowledge of ML workflows and productionization.
- Experience with monitoring tools such as Splunk or Datadog.
- Strong troubleshooting and collaboration skills.