Lead DevOps/MLOps Engineer

We are seeking a driven and highly skilled Lead DevOps/MLOps Engineer to assess client infrastructure to enable the deployment of Enterprise Data Platform (EDP) components, aiming to ensure seamless integration and operational efficiency for a leading company in the oil and gas industry. The focus is on evaluating existing systems and preparing them for a scalable data platform rollout. Responsibilities Conduct comprehensive assessments of client infrastructure for EDP 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 feedback for optimization Support continuous improvement of deployment processes and infrastructure standards Requirements 5+ years in DevOps / Data Engineering, including technical or team leadership experience Expertise in infrastructure assessment and readiness evaluation for data platform deployments Proficiency in DevOps practices tailored to data engineering environments Background in deploying platform and application workloads on Kubernetes Knowledge of EDP components and their deployment requirements, along with CI/CD and Argo Ability to analyze complex client environments and identify potential integration challenges Experience collaborating within cross-functional teams and coordinating with external vendors English proficiency at an Upper-Intermediate level (B2) or higher Nice to have Familiarity with MLflow, Airflow, and automated retraining Skills in data quality and monitoring tools Competency in Docker Experience with Linux Knowledge of Python Understanding of machine learning and agentic AI applications, and what it takes to deploy and run them reliably in production