Data Migration Architect - Teamcenter
Capgemini · Seattle, WA · 6 days ago
Full-time
About the role
You're considering Capgemini is seeking a highly experienced Data Migration Architect to serve as the technical authority for a large-scale Siemens Teamcenter PLM modernization program supporting a major Aerospace & Defense client.
Responsibilities
- Define and govern the end-to-end migration architecture, including data extraction, transformation, validation, reconciliation, quality controls, and migration performance across a global delivery model.
- Design scalable migration pipelines, workflows, and system integrations capable of supporting large-volume, complex engineering datasets.
- Establish data quality frameworks including profiling, cleansing, anomaly detection, validation, and auditability throughout the migration lifecycle.
- Drive migration sizing, throughput optimization, performance tuning, and risk mitigation activities to ensure successful program delivery.
- Collaborate with business stakeholders, engineering teams, PLM architects, and global delivery teams to align migration architecture with program objectives.
- Leverage AI-assisted approaches for data profiling, mapping acceleration, anomaly detection, and migration quality improvement while maintaining traceability and governance.
Requirements
- 15+ years of experience in Data Architecture, Migration Architecture, or Enterprise Data Transformation with a proven track record delivering large-scale migration programs.
- Deep hands-on expertise with Siemens Teamcenter data models, PLM architectures, and migration of data from legacy PDM systems.
- Strong experience with data quality management, profiling, cleansing, reconciliation, validation frameworks, and migration governance controls.
- Demonstrated success leading migration architecture across global onshore-offshore delivery teams and complex enterprise environments.
- Experience within Aerospace & Defense, Manufacturing, or other highly regulated industries; exposure to AI-enabled migration and data quality solutions is strongly preferred.