Senior Data Engineer: MLOps & Data Pipelines

EPAM Systems; Colombia; Presencial; COP 100.440.000 - 167.400.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Healthcare benefits

Global career opportunities

Paid time off

Descripción de la vacante

EPAM Systems is seeking a Senior Data Engineer to lead design, development, and upkeep of data and ML pipelines on Domino Data Lab. The role focuses on data engineering and MLOps, building dependable pipelines, managing model lifecycles, and ensuring secure, efficient platform operations.

The candidate will work with cross-functional teams, implement automation, and contribute to platform improvements. This position requires at least 3 years of hands-on experience and strong Python/SQL skills.

Formación

• At least 3 years of relevant experience.
• Proficient in Python for data engineering and pipeline development.
• Strong SQL skills across relational and data warehouse systems.
• Experience with Docker and Kubernetes for deploying data workloads.
• CI/CD experience with Jenkins, GitHub Actions, or Azure DevOps.
• Cloud familiarity with AWS, Azure, or GCP.
• Excellent English proficiency (B2 or higher).

Responsabilidades

• Build and maintain reliable data pipelines powering analytics and ML workloads.
• Manage end-to-end data workflows: ingestion, transformation, and delivery.
• Oversee compute infrastructure to keep platforms secure and efficient.
• Collaborate with data scientists and engineers on tooling requirements.
• Promote best practices for platform usage and data workflows.
• Automate testing and deployment to improve reliability.
• Document designs, workflows, and configurations for knowledge sharing.

Conocimientos

Python

SQL

Bash

R

ETL/ELT

CI/CD

English (B2+)

Herramientas

Docker

Kubernetes

Jenkins

GitHub Actions

GitLab CI

Azure DevOps

Descripción del empleo

EPAM Systems is seeking a Senior Data Engineer to lead design, development, and upkeep of data and ML pipelines on Domino Data Lab. The role focuses on data engineering and MLOps, building dependable pipelines, managing model lifecycles, and ensuring secure, efficient platform operations.

The candidate will work with cross-functional teams, implement automation, and contribute to platform improvements. This position requires at least 3 years of hands-on experience and strong Python/SQL skills.