Senior Data Engineer

EPAM Systems; Mexico; On-site; PHP 4,514,000 - 6,897,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off and sick leave

Upskilling and certification courses

LinkedIn Learning access

Global career opportunities

Job summary

EPAM Systems is seeking a Senior Data Engineer to head the design, development, and upkeep of data and ML pipelines on the Domino Data Lab platform. This role centers on data engineering and MLOps, building reliable data pipelines and managing compute infrastructure to keep the platform running efficiently and securely.

The ideal candidate will have 3+ years of experience, expert Python, strong SQL, and hands-on Kubernetes, Docker, and CI/CD experience, plus cloud familiarity.

Qualifications

• At least 3 years of relevant experience.
• Deep hands-on experience with the Domino Data Lab platform (Data Sources, Datasets, Environments, Projects, Jobs, Flows).
• Expert-level Python for data engineering and pipeline development.
• Strong SQL skills for data extraction, transformation and optimization.
• Familiarity with Bash, R; scripting automation.
• Experience building and maintaining ETL/ELT pipelines.
• Kubernetes experience with EKS/AKS/GKE; deploy and fine-tune data/ML workloads.
• Docker for data/ML workloads; container images.
• CI/CD pipelines using Jenkins, GitLab CI, GitHub Actions or Azure DevOps.
• Experience with at least one major cloud provider (AWS/Azure/GCP).
• Excellent English proficiency (B2+).

Responsibilities

• Build and sustain dependable data pipelines powering analytics and ML workloads.
• Handle end-to-end data workflows: ingestion, transformation, delivery.
• Manage compute infrastructure to keep platform operations efficient and secure.
• Diagnose and resolve pipeline performance and data quality issues.
• Collaborate with data scientists and engineers on infrastructure needs.
• Define and champion best practices for platform usage and data workflows.
• Automate testing and deployment to boost reliability.
• Monitor pipeline health and preempt bottlenecks or failures.
• Drive improvements to internal tools and processes for data ops.
• Record designs and configurations to enable knowledge sharing.

Skills

Python

SQL

Bash

R

Docker

Kubernetes

CI/CD

Cloud platforms

Tools

Jenkins

GitLab CI

GitHub Actions

Azure DevOps

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 looking for a Senior Data Engineer to head the design, development, and upkeep of data and ML pipelines on the Domino Data Lab platform. This position centers on the data engineering and MLOps aspects of Domino, constructing dependable data pipelines, overseeing model lifecycle workflows, and keeping the platform's data and compute infrastructure running efficiently and securely. This is not a front-end or application development role.

Responsibilities

• Build and sustain dependable data pipelines that power analytical and machine learning workloads
• Handle the full lifecycle of data workflows, spanning ingestion, transformation, and delivery
• Manage compute infrastructure to keep platform operations efficient, secure, and dependable
• Diagnose and resolve issues that affect pipeline performance and data quality
• Work alongside data scientists and other engineers to meet their infrastructure and tooling requirements
• Define and champion best practices around platform usage, pipeline design, and data workflow structure
• Introduce automation into testing and deployment processes to boost reliability and cut down manual workKeep watch over pipeline health and get ahead of bottlenecks or failures before they escalation
• Help drive continuous improvement of internal tools and processes that support data operations
• Record technical designs, workflows, and configurations to enable knowledge sharing throughout the team

Requirements

• At least 3 years of relevant experience
• Deep hands-on experience with the Domino Data Lab platform, including Data Sources and Connectors, Datasets, Environments, Projects, Jobs, and Flows, with the ability to architect and troubleshoot end-to-end data pipelines and promote best practices for platform usage
• Expert-level command of Python as the main language for data engineering and pipeline development
• Strong SQL skills for extracting, transforming, and optimizing data across relational and warehouse systems
• Comfortable using R and Bash across the wider data science toolchain and for scripting automation
• Proven experience designing, constructing, and maintaining ETL/ELT pipelines, including data ingestion, transformation, validation, and orchestration
• Practical experience with Kubernetes and managed offerings such as EKS, AKS, or GKE, with the ability to deploy, debug, and fine-tune cluster workloads running data and ML jobs
• Experience creating, optimizing, and troubleshooting container images for data and ML workloads using Docker
• Experience establishing and maintaining CI/CD pipelines using tools such as Jenkins, GitLab CI, GitHub Actions, or Azure DevOps to automate testing and deployment of data pipelines and ML workflows
• Working familiarity with at least one major cloud provider, such as AWS, Azure, or GCP, with the ability to evaluate data architecture, cost, and security trade-offs
• Excellent English proficiency (B2 level or higher)

Nice to have

• Experience with Domino Nexus or hybrid/multi-cloud compute orchestration
• Experience delivering ML workflows spanning training, deployment, monitoring, and retraining, with an understanding of reproducibility and versioning
• Practical experience with GenAI, LLMs, or agentic frameworks, including retrieval-augmented generation (RAG), from a data pipeline perspective
• Familiarity with orchestration tools such as MLflow, Kubeflow, Airflow, or Domino Flows
• Knowledge of model governance, compliance automation, or audit logging frameworks
• Experience working within pharma, BFSI, or public sector environments

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 opportunities
• EPAM 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.