Why this role stands out
This hybrid role at EPAM Systems offers an exceptional opportunity to advance your career in Data DevOps, building and scaling cutting-edge data platforms on Azure and Databricks within a collaborative environment. You'll thrive here if you possess strong Azure, Databricks, and CI/CD pipeline experience, enjoy problem-solving, and are eager to contribute to robust data solutions. Apply now to leverage your skills and grow with a leading technology company!
Quick overview
Job description
We are seeking a highly skilled Senior Data DevOps Engineer specializing in Azure to join our team and drive the deployment, configuration, and optimization of data platforms and workflows. This role combines technical expertise with collaboration, paving the way for scalable and secure data solutions.
Responsibilities Deploy and configure the Data Platform in Databricks based on the approved architecture and solution designs, ensuring environments are production-ready, secure, and scalable Work closely with cross-functional teams (Data Engineering, ML, Platform, QA) to design, implement, and evolve CI/CD pipelines and supporting tooling for data workflows and services Diagnose and resolve issues in build/deploy pipelines, data workflows, and production workloads; participate in root cause analysis and implement preventive fixes Develop, standardize, and maintain configuration management practices (infrastructure configuration, environment parameters, secrets, cluster policies) to ensure consistency across environments Produce and maintain clear technical documentation covering deployment guides, operational runbooks, pipeline logic, and platform configuration Requirements 3+ years of experience in a Build Engineer, DevOps Engineer, Platform Engineer, or similar role supporting delivery and operations Strong hands-on experience with Databricks, Azure Data Factory, Azure DevOps, and Microsoft Azure in general - including DataOps practices such as automated data pipeline deployment, environment promotion, and governance Strong communication and collaboration skills, with the ability to work effectively across engineering, data, and operations teams English at B2 level or higher, ability to participate in technical discussions and produce documentation in English Nice to have Experience with MLOps (model deployment, monitoring, lifecycle automation for ML workloads)
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