Data Analyst; on-site

Job Title

Senior Data Analyst (D365 Migration & Data Integration)

$75,000 – $85,000 (depending on experience)

This role supports a major ERP migration involving Dynamics 365 F&O, CE, and a proprietary internal platform. You’ll be responsible for ensuring accurate, clean, and synchronized data ahead of a company wide go‑live.

• High‑impact role tied directly to a strategic technology rollout
• Strong ownership of cross‑system data quality
• Work closely with technical leads, DBAs, and project managers
• Opportunity to establish data hygiene and migration best practices
• Long‑term contract with strong likelihood of extension

• Clean, audit, and reconcile data across D365 and connected systems
• Validate data accuracy and completeness on a regular basis

• Support ongoing data syncs between multiple platforms
• Review results and resolve any mismatches or errors

• Assist with end‑to‑end data migration tasks
• Run and monitor ETL processes using SQL, SSRS, and Excel
• Participate in pre‑go‑live testing and cutover preparation

• Work with DBAs, API teams, and project leadership
• Provide clear reporting on data quality and migration status
• Troubleshoot data issues quickly in a fast‑moving environment

• Hands‑on Dynamics 365 implementation experience (mandatory)
  • D365 Finance & Operations required
  • CE experience preferred
• Strong ETL, SQL, SSRS, and intermediate‑to‑advanced Excel skills
• Experience with data cleanup, auditing, and reconciliation
• Comfortable working independently with limited supervision
• Strong communication skills and ability to operate under deadlines

• Experience with Python or Azure Databricks
• Familiarity with CE or other ERP/data systems
• Experience collaborating with API or database engineering teams
• Background supporting ERP cutovers or complex migrations

• High visibility with senior leadership
• Direct impact on a major ERP go‑live
• Ownership of key data deliverables
• Strong contract stability with the potential for long‑term work
• Opportunity to influence future data practices and process improvements