DevOps/MLOps Engineer for Enterprise Data Platform

The role supports the deployment of Enterprise Data Platform components for a leading oil and gas company, focusing on assessing existing infrastructure and preparing it for a scalable data platform rollout.

• Assess client infrastructure for Enterprise Data Platform rollout feasibility
• Identify and document infrastructure gaps and recommend remediation actions
• Collaborate with data engineering and DevOps teams to align deployment strategies
• Develop and maintain deployment automation scripts and tools
• Coordinate with third-party vendors to ensure compatibility and support
• Monitor infrastructure performance and provide optimization feedback
• Improve deployment processes and infrastructure standards
• Deploy platform and application workloads on Kubernetes

• 5+ Years of experience in DevOps practices tailored to data engineering environments
• Expertise in infrastructure assessment and readiness evaluation for data platform deployments
• Knowledge of Enterprise Data Platform components and their deployment requirements
• Ability to analyze complex client environments and identify potential integration challenges
• Experience collaborating within cross-functional teams and coordinating with external vendors
• Proficiency in Docker, Kubernetes, and Linux
• Skills in CI/CD, Argo, and Python
• Understanding of machine learning and agentic AI applications and the requirements for running them reliably in production
• English proficiency at B2 level or higher
• Будет плюсом: Background in MLflow and Airflow, knowledge of automated retraining tools, exposure to data quality and monitoring tools

• Условий в вакансии нет