Senior Data Engineer

EPAM Systems; Bogotá ciudad; On-site; COP 120,000,000 - 180,000,000; Full time

Benefits offered by this job

Healthcare benefits

Professional development

Paid time off

Flexible work options

Global team exposure

Job summary

EPAM Systems in Bogotá is seeking a Senior Data Engineer to build an MLOps platform and enable automated model delivery, deployment, and feature engineering at scale using Azure Databricks, Azure Data Factory, and Azure DevOps.

You will migrate Spark pipelines to Azure, collaborate with Data Scientists, and help design CI/CD feeding the Databricks Feature Store, contributing to scalable data pipelines and production ML workflows.

Qualifications

• 3+ years hands-on PySpark experience.
• Strong Data Science fundamentals.
• Proven track record in ML feature engineering and pipelines.
• Experience migrating pipelines to cloud environments.
• English proficiency at B2 level or higher.

Responsibilities

• Migrate Spark feature engineering pipelines to Azure.
• Collaborate to define and build forecasting models.
• Assist deploying ML models to production.
• Design CI/CD for Databricks Feature Store.
• Work with data scientists and engineers to align features with model needs.
• Maintain scalable data pipelines across the platform.

Skills

PySpark

Data Science

ML pipeline development

Cloud data pipelines

CI/CD

Collaboration with data scientists

Tools

MLflow

Docker

Azure Kubernetes Service

Azure Data Factory

Azure Databricks

Job description

EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.

We are seeking a Senior Data Engineer to build an MLOps platform and enable automated model delivery, deployment, and feature engineering at scale. You will evolve the featureOps stack using Azure Databricks, Azure Data Factory, and Azure DevOps to run CI/CD into the Databricks Feature Store for Model Lab use cases.

Responsibilities

• Migrate current Spark feature engineering pipelines to Azure
• Partner with the team to define and build a forecasting model
• Assist with taking the developed machine learning model into production
• Help design and implement the CI/CD pipeline that feeds the Databricks Feature Store
• Collaborate closely with Data Scientists and engineers to match feature engineering to ML model needs
• Maintain reliability and scalability of data pipelines across the platform
• Diagnose and improve existing Spark-based workflows throughout the migration

Requirements

• Hands‑on experience of 3+ years working with PySpark
• Solid background in Data Science core skills
• Proven track record in feature engineering and machine learning pipeline development
• Practical experience migrating data pipelines to cloud environments
• English proficiency at B2 (Upper‑Intermediate) level or higher

Nice to have

• Experience with MLflow and Docker
• Working knowledge of Azure Kubernetes Services, Azure Data Factory, and Azure Databricks
• Familiarity with ML model deployment practices

We offer

• 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 opportunitiesEPAM Employee Groups
• Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn

EPAM 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.