Data Engineer

EPAM Systems; México; Remote; MXN 520,000 - 760,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

Learning & development

Global career opportunities

Job summary

EPAM Systems, Inc. seeks a Data Engineer to join a team building an MLOps platform that automates model development, deployment, and feature engineering. You will migrate Spark pipelines to Azure and collaborate to forecast models.

You will deploy ML models to production, design CI/CD for the Databricks Feature Store, and ensure scalable, robust data pipelines in a dynamic, global environment.

Qualifications

• 2+ years of experience with PySpark.
• Strong Data Science core skills and ML pipeline development.
• Experience migrating data pipelines to cloud environments.
• English proficiency at B2 level or higher.

Responsibilities

• Migrate existing Spark feature engineering pipelines to Azure.
• Collaborate with the team to identify and develop forecasting models.
• Support deployment of ML models to production.
• Design and develop CI/CD pipelines feeding the Databricks Feature Store.
• Work with Data Scientists and engineers to align feature engineering with ML model requirements.
• Ensure reliability and scalability of data pipelines across the platform.

Skills

PySpark

Data Science

Feature engineering

ML pipeline

English (B2+)

Tools

Azure Databricks

Azure Data Factory

Azure DevOps

MLflow

Docker

Azure Kubernetes Services

Job description

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.ResponsibilitiesMigrate existing Spark feature engineering pipelines to AzureCollaborate with the team to identify and develop a forecasting modelSupport the deployment of the developed machine learning model to productionContribute to the design and development of the CI/CD pipeline feeding the Databricks Feature StoreWork closely with Data Scientists and engineers to align feature engineering with ML model requirementsEnsure the reliability and scalability of data pipelines across the platformTroubleshoot and optimize existing Spark-based workflows during migrationRequirements2+ years of experience working with PySparkStrong background in Data Science core skillsProficiency in feature engineering and machine learning pipeline developmentExperience migrating data pipelines to cloud environmentsEnglish proficiency at B2 level or higherNice to haveFamiliarity with MLflow and DockerKnowledge of Azure Kubernetes Services, Azure Data Factory, and Azure DatabricksUnderstanding of ML model deployment practicesWe offerInternational projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedInEPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.