Our Customer:
A global enterprise organization building modern data, analytics, and AI solutions within a Microsoft-first ecosystem. The company focuses on scalable and secure enterprise platforms that support business intelligence and digital transformation.
Your Tasks:
Develop and manage release plans across multiple PODs, including release deliverables, features, timelines, and scope.
Support Teva-related processes covering data availability, architecture approvals, risk management, and compliance reviews.
Coordinate dependency planning and scope alignment across multiple PODs.
Identify and support the resolution of dependencies and conflicts between teams and PODs.
Support prioritization and approval processes related to environment setup, data availability, and other release-related activities.
Identify, assess, and support mitigation of risks associated with releases.
Participate in Go/No-Go decisions and coordinate release-related communication from the Teva side.
Coordinate release activities across cross-functional teams and stakeholders to support successful release execution.
Required Experience and Skills:
5+ years of experience in Release Management, Release Engineering, Release Coordination, RTE, or a similar role.
Strong understanding of CI/CD pipelines.
Strong understanding of DevOps practices.
Experience with release orchestration and automation tools.
Experience with version control.
Experience with configuration management.
Good knowledge of Agile frameworks.
Good knowledge of Scrum.
Good knowledge of ITIL frameworks.
Experience coordinating cross-functional teams.
Experience managing complex dependencies across multiple teams or PODs.
Proven experience in risk assessment within release processes.
Experience with risk mitigation.
Strong problem-solving skills.
Experience participating in Go/No-Go decisions.
Experience coordinating release approval processes.
Strong communication skills.
Strong stakeholder coordination skills.
Knowledge and understanding of Data projects.
Knowledge and understanding of AI projects.
Would Be a Plus:
Experience with MLOps / DataOps tools and environments, such as MLflow, Airflow, or similar technologies.
Experience coordinating releases for Data or AI projects.
Experience working in a highly regulated enterprise environment.
Experience with large-scale Agile environments involving multiple teams or PODs.
Experience with SAFe / Release Train Engineer (RTE) practices.
