platform engineer for data platforms

EPAM provides enterprise software products, open source solutions, and technology accelerators.

• Own the data platform architecture by designing, evolving, and scaling 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 infrastructure reliability, security, and cost-efficiency through SLAs, observability, and cost optimization;
• Partner with data engineers, analysts, DS/ML teams, product, and security stakeholders.

• 5+ Years of experience in DevOps or 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, or Azure, including its data services;
• Experience with Docker, Kubernetes, and Terraform or equivalent IaC;
• Experience with pipeline orchestration using Airflow, Dagster, Prefect, or equivalent;
• Experience with big data and streaming technologies, including Spark, Kafka, data lakes, and DWHs such as Snowflake, BigQuery, or Redshift;
• Experience with Python and/or Scala, strong SQL, and bash;
• Experience setting up monitoring and observability with Prometheus, Grafana, ELK, or equivalent;
• Experience with LLM/GenAI infrastructure and serving;
• Knowledge of data governance, security, and data compliance;
• Experience with cloud cost optimization (FinOps).

• Remote work is available from Türkiye.