We are looking for a Lead Data DevOps Engineer to architect and run reliable data and ML pipelines on the Domino Data Lab platform, ensuring secure and efficient compute and data infrastructure. You will guide best practices across pipeline engineering, Kubernetes operations, and delivery automation. Apply now to help raise platform reliability and speed.

Responsibilities Lead the design of end-to-end data and ML pipelines on the Domino Data Lab platform

Architect secure and scalable patterns for data ingestion, transformation, validation, and orchestration

Build and maintain Domino projects, environments, datasets, jobs, connectors, and flows to support production workflows

Operate Kubernetes-based workloads for data and ML jobs, including deployment, debugging, and performance tuning

Create and optimize Docker images for reproducible data and ML execution

Implement CI/CD automation for testing, release, and deployment of pipelines and workflow artifacts

Define best practices and guardrails for reliability, security, cost awareness, and reproducibility

Troubleshoot pipeline failures and platform issues, drive root-cause analysis, and implement preventive fixes

Collaborate with stakeholders to translate requirements into technical designs and delivery plans

Mentor engineers on Domino usage, pipeline patterns, and operational excellence

Document architectures, runbooks, and operating procedures for ongoing support

Improve monitoring and operational visibility for data and ML workflows

Ensure solutions align with compliance-minded practices expected in regulated domains Requirements 5+ years of experience in data software engineering and pipeline delivery





Expert-level Domino Data Lab expertise with Data Sources, Datasets, Environments, Projects, Jobs, and Flows

5+ years of experience with Python for data engineering and automation

Strong SQL skills for extraction, transformation, and optimization

Hands-on Kubernetes experience with workload deployment, debugging, and tuning (including managed offerings)

Strong containerization skills with Docker image build and troubleshooting

Proven CI/CD experience for data and ML pipelines using modern automation tools

Strong leadership skills to set standards, mentor peers, and drive technical decisions

Strong project ownership skills to plan, prioritize, and deliver end-to-end improvements

Strong stakeholder communication skills with a consultative, direct approach

Upper-Intermediate English proficiency (B2)

Experience working in Pharma & Biotech environments Nice to have Amazon Web Services experience for data and ML platform architecture

MLOps experience across training, deployment, monitoring, and retraining workflows

MLflow experience for experiment tracking and lifecycle coordination

Gen AI Application Development experience focused on RAG and data pipelines We offer International projects with top brands

Work with integral 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

📌 Lead Data DevOps Engineer (Domino Data Lab) (Argentina)
🏢 EPAM Systems
📍 Argentina