Description

You will build and manage the data infrastructure required to support production machine learning models.

Responsibilities

• Set up and manage Unity Catalog in Databricks to organize and secure data access across teams.
• Design and operationalize Feature Stores to support machine learning models in production.
• Build efficient data pipelines to process and serve features to ML workflows.
• Collaborate with teams using Databricks, Azure Cosmos DB, and other Azure tools to integrate data solutions.
• Monitor and optimize the performance of pipelines and feature stores.

Required Skills

• 5+ years of experience in machine learning or data engineering roles.
• Strong experience with Unity Catalog in Databricks for managing data assets and access control.
• Hands-on experience working with Databricks Feature Store or similar solutions.
• Knowledge of building and maintaining scalable ETL pipelines in Databricks.
• Proficiency in Python and Spark for data engineering tasks.
• Familiarity with Azure tools including Azure Cosmos DB and ACR.
• Understanding of machine learning workflows and feature store integration.
• Experience with monitoring tools like Splunk or Datadog.
• Familiarity with AKS for deploying and managing containers.

Key Skills

Education

Any Graduate