Data Engineer

About the role

EPAM is seeking a Data Engineer to join the team developing an MLOps platform that automates machine learning model development, deployment, and feature engineering. The role focuses on building and migrating feature engineering pipelines using Azure services.

Key responsibilities

• Migrate existing Spark feature engineering pipelines to Azure.
• Collaborate with the team to identify and develop forecasting models.
• Support the deployment of machine learning models to production.
• Contribute to the design and development of the CI/CD pipeline feeding the Databricks Feature Store.
• Work closely with Data Scientists and engineers to align feature engineering with ML model requirements.
• Ensure reliability and scalability of data pipelines across the platform.
• Troubleshoot and optimize existing Spark‑based workflows during migration.

Required profile

• 2+ years of experience working with PySpark.
• Strong background in core Data Science skills.
• Proficiency in feature engineering and machine learning pipeline development.
• Experience migrating data pipelines to cloud environments.
• English proficiency at B2 level or higher.

Required skills

• PySpark
• Azure Databricks
• Azure Data Factory
• Azure DevOps
• MLflow (nice to have)
• Docker (nice to have)
• Azure Kubernetes Services (nice to have)

What we offer

• International projects with top brands.
• Work with global, diverse teams.
• Healthcare benefits.
• Employee financial programs.
• Paid time off and sick leave.
• Upskilling, reskilling and certification courses.
• Unlimited access to LinkedIn Learning library.
• Global career opportunities.
• Volunteer and community involvement opportunities.
• Award‑winning culture recognized by Glassdoor, Newsweek and LinkedIn.