Data DevOps Lead

EPAM Systems Inc; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

EPAM Systems is seeking a Data DevOps Lead to own the data platform infrastructure, CI/CD for data pipelines and ML models, and to establish DataOps practices. You will lead a small team of engineers and set technical standards at the intersection of data engineering, DevOps, and leadership.

You will design scalable data platform architecture, implement IaC, monitoring, security, and cost optimization, collaborating with data engineers, analysts, DS/ML teams, product and security to drive

Qualifications

• 5+ years in DevOps / Data Engineering, including leadership experience
• Hands-on AI/ML infra experience in production (MLOps)
• Strong command of a cloud platform (AWS / GCP / Azure) and its data services
• Experience with Docker, Kubernetes, Terraform (IaC)
• Experience with pipeline orchestration (Airflow, Dagster, Prefect)
• Experience with big data and streaming (Spark, Kafka, Snowflake/BigQuery/Redshift)
• Proficient in Python/Scala, SQL, and bash
• Monitoring/observability setup (Prometheus, Grafana, ELK)
• Experience with LLM/GenAI infra and serving
• Data governance, security, and cost optimization (FinOps)

Responsibilities

• Own the data platform architecture, design, evolve, and scale the data infrastructure
• Build and maintain CI/CD processes for data pipelines, infrastructure, and ML models
• Implement Infrastructure as Code, versioning, automated testing, and data monitoring practices
• Define the technical roadmap and standards, manage technical debt
• Ensure reliability, security, and cost-efficiency of the infrastructure (SLAs, observability)
• Partner with data engineers, analysts, DS/ML teams, product, and security

Skills

Leadership

Data platform design

CI/CD for data

MLOps

Cloud architecture

Python/Scala

SQL

Monitoring/observability

FinOps

Tools

Docker

Kubernetes

Terraform

Airflow

Dagster

Prefect

Spark

Kafka

Snowflake

BigQuery

Redshift

Prometheus

Grafana

ELK

Job description

The Data DevOps Lead owns the infrastructure and delivery processes for data: building and evolving the data platform, establishing CI/CD and DataOps practices, leading a small team of engineers, and setting technical standards. This role sits at the intersection of data engineering, DevOps, and team leadership.

Responsibilities

• Own the data platform architecture: design, evolve, and scale the infrastructure for data pipelines
• Build and maintain CI/CD processes for data pipelines, infrastructure, and ML models
• Implement Infrastructure as Code, versioning, automated testing, and data monitoring practices
• Define the technical roadmap and standards, and manage technical debt
• Ensure reliability, security, and cost-efficiency of the infrastructure (SLAs, observability, cost optimization)
• Partner with stakeholders: data engineers, analysts, DS/ML teams, product, and security

Requirements

• 5+ years in DevOps / Data Engineering, including technical or team leadership experience
• Hands‑on experience with AI/ML infrastructure and supporting AI/ML workloads in production (MLOps)
• Strong command of one cloud platform (AWS / GCP / Azure) and its data services
• Docker, Kubernetes, Terraform (or equivalent IaC)
• Pipeline orchestration (Airflow, Dagster, Prefect, or equivalent)
• Experience with big data and streaming: Spark, Kafka, data lake / DWH (Snowflake, BigQuery, Redshift, etc.)
• Languages: Python and/or Scala, strong SQL, bash
• Monitoring and observability setup (Prometheus, Grafana, ELK, etc.)
• Experience with LLM/GenAI infrastructure and serving
• Data governance, security, and data compliance
• Cloud cost optimization (FinOps)