About The Position

Lead the end-to-end execution of a large-scale IBM DataStage to Microsoft Fabric modernization program, coordinating architecture, engineering, migration, testing, deployment, and business stakeholders. Own program planning, execution governance, dependencies, risks, customer communication, and delivery outcomes. This role drives planning across assessment, architecture, migration, engineering, testing and user acceptance testing, deployment, and production readiness. It partners with Fabric architects and engineering leads on migration scope, DataStage job dependencies, solution design, and technical decisions. The position also coordinates data engineering, architecture, DevOps, QA, business, and customer teams, and drives release planning, cutover readiness, operational handover, and post-production stabilization.

Requirements

  • Technical program management experience and skills.
  • Strong customer-facing, stakeholder management, and executive communication skills.
  • Ability to challenge technical teams, understand architecture discussions, and translate technical issues into clear program actions.

Nice To Haves

  • Strong experience managing enterprise data platform modernization/migration programs.
  • Good working knowledge of Microsoft Fabric and Azure Data Platform.
  • Exposure to IBM DataStage migration/modernization programs.
  • Experience managing complex programs involving multiple engineering workstreams and dependencies.
  • Microsoft Fabric/Azure certifications are a plus.

Responsibilities

  • Own end-to-end program execution for DataStage-to-Microsoft Fabric modernization.
  • Drive planning across assessment, architecture, migration, engineering, testing/UAT, deployment, and production readiness.
  • Partner with Fabric Architects and engineering leads on migration scope, DataStage job dependencies, solution design, and technical decisions.
  • Manage program milestones, RAID, dependencies, deliverables, and critical path.
  • Establish execution governance, status reporting, metrics, and leadership/customer reviews.
  • Coordinate across data engineering, architecture, DevOps, QA, business, and customer teams.
  • Drive environment, access, infrastructure, and deployment readiness.
  • Ensure technical blockers and cross-team dependencies are identified early, assigned clear owners, and driven to closure.
  • Track migration progress and ensure delivery quality against agreed scope and timelines.
  • Provide clear executive and customer communication on progress, risks, decisions, and required actions.
  • Drive release planning, cutover readiness, operational handover, and post-production stabilization.
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