Data Engineer

We are seeking a Data Engineer to join a team developing an MLOps platform that automates machine learning model development, deployment, and feature engineering. The featureOps component of the platform leverages Azure Databricks, Azure Data Factory, and Azure DevOps to build a CI/CD pipeline that feeds the Databricks Feature Store, with generated features used for ML model development in Model Lab.

Responsibilities

• Migrate existing Spark feature engineering pipelines to Azure
• Collaborate with the team to identify and develop a forecasting model
• Support the deployment of the developed machine learning model 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 the reliability and scalability of data pipelines across the platform
• Troubleshoot and optimize existing Spark-based workflows during migration

Requirements

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

Nice to have

• Familiarity with MLflow and Docker
• Knowledge of Azure Kubernetes Services, Azure Data Factory, and Azure Databricks
• Understanding of ML model deployment practices

Benefits

• International projects with top brands
• Work with global teams of highly skilled, diverse peers
• Healthcare benefits
• Employee financial programs
• Paid time off and sick leave
• Upskilling, reskilling and certification courses
• Unlimited access to the LinkedIn Learning library and 22,000+ courses
• Global career opportunities
• Volunteer and community involvement opportunities
• EPAM Employee Groups
• Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn