Microsoft Fabric Data Architect

Hello,
UnivEdge Consulting is hiring for one of our direct clients - a global technology consulting leader based in the US. Immediate interviews for the below position.
Microsoft Fabric Data Architect (DataStage to Fabric Migration)
Location: Remote
Engagement: Contract
About the role
The client is looking for a hands-on Data Architect to lead the migration of an existing IBM DataStage ETL estate to Microsoft Fabric. The architect will own the target-state design, the migration approach, and delivery guidance for the engineering team, from assessment through cutover.
Key responsibilities
Assess the current DataStage landscape, including jobs, sequences, transformers, parameter sets, and dependencies, and build a migration inventory and complexity map.
Design the target architecture on Microsoft Fabric: OneLake, Lakehouse/Warehouse, Data Factory pipelines, Dataflows Gen2, and Spark notebooks.
Define migration patterns that map DataStage stages and logic to Fabric equivalents, plus a strategy for rewrite, re-platform, or retire.
Set standards for data modeling (medallion/layered architecture), naming, orchestration, error handling, and performance tuning.
Plan and oversee data validation and reconciliation between legacy and target outputs, parallel runs, and cutover.
Establish governance, security, and lineage (workspace strategy, access control, Purview integration).
Set up CI/CD and deployment practices for Fabric artifacts (Git integration, deployment pipelines).
Guide and review the work of data engineers, and act as the technical point of contact for client stakeholders.
Must-have skills
12+ years in data engineering/ETL, with 3+ years in a data architect role.
Strong hands-on experience with Microsoft Fabric (Lakehouse, Warehouse, Data Factory pipelines, notebooks, OneLake).
Solid working knowledge of IBM DataStage: parallel jobs, sequences, transformer logic, and reading or reverse-engineering existing jobs.
Proven experience delivering at least one ETL migration to a cloud platform.
Strong SQL and PySpark/Spark SQL.
Data modeling expertise (dimensional, medallion).
Good to have
Azure Synapse, Azure Data Factory, or Databricks experience.
Power BI with Direct Lake / semantic models.
Microsoft Purview, Azure DevOps/GitHub CI/CD.
Certifications: DP-600 (Fabric Analytics Engineer), DP-700 (Fabric Data Engineer), or Azure Data Engineer/Architect.
Experience with automated migration or code-conversion tools.

Work arrangement
Yes