Data Migration Architect

INFOSYS NOVA HOLDINGS LLC•Seattle, WA
•$100,000 - $150,000

About The Position

We are seeking an experienced Data Migration Architect to lead the strategy, architecture, and execution of data migration for a large-scale Teamcenter implementation. This individual will own the migration approach from legacy-system assessment and source-to-target mapping through mock migrations, production cutover, reconciliation, and hypercare. The ideal candidate will have deep experience with Teamcenter data models, PLM data migration, ETL processes, legacy data transformation, and enterprise-scale migration programs. Experience with Teamcenter X and Medical Device/Life Sciences environments is highly preferred.

Requirements

  • 8–12 years of experience with PLM, enterprise data migration, or related technologies.
  • Teamcenter migration architecture
  • Legacy data assessment
  • Migration framework design
  • Teamcenter source-to-target mapping

Nice To Haves

  • Experience with Teamcenter X SaaS is a strong plus.
  • Medical Device, Life Sciences, or another highly regulated industry background is preferred.
  • Experience migrating data from platforms such as Agile PLM, TrackWise, SolidWorks PDM Vault, Autodesk Vault, Altium 365, SharePoint, or Documentum is highly desirable.

Responsibilities

  • Define the end-to-end Teamcenter data migration architecture, strategy, and roadmap.
  • Assess legacy systems, perform data profiling, and determine migration scope and data quality.
  • Design source-to-target mappings for Teamcenter objects including Items, Revisions, BOMs, Documents, CAD data, Workflows, Change Objects, and Classification data.
  • Define strategies for data cleansing, transformation, enrichment, deduplication, archival, and retention.
  • Design and oversee data extraction, staging, validation, reconciliation, and loading processes.
  • Develop or lead development of migration scripts, utilities, automation tools, and accelerators.
  • Plan and execute mock migrations, production cutovers, rollback strategies, and post-go-live support.
  • Ensure data integrity, traceability, referential consistency, auditability, and regulatory compliance.
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