Data Analyst

Essential Duties and Responsibilities

• Data Assessment and Deployment Readiness
• - Profile legacy/source data, assessing source-system readiness, and identifying data dependencies, gaps, and quality issues for upcoming deployment waves.
• - Use SQL to extract, join, validate, compare, and reconcile datasets from source systems, staging files, and target structures.
• - Build and maintain source-to-target mapping workbooks, data-quality issue logs, reconciliation workpapers, and extraction inventories.
• - Support repeatable migration playbooks, file-governance standards, naming conventions, and handoff procedures that can scale across multiple OpCos.

Business Process & Requirements

• - Translate business rules, legacy field usage, and entity-specific process differences into clear mapping logic, transformation rules, and documented requirements.
• - Partner with business stakeholders to understand how source data is created, maintained, and used operationally, then assess fit against target-state requirements.
• - For later go-live waves, own the data workstream for one OpCo covering extraction, analysis, assessment, mapping, offline migration activities, issue resolution follow-up, and stakeholder communication.
• - Contribute to standard templates and reusable practices so that later waves are faster, more consistent, and less dependent on one-off decisions.

Delivery & Cross-Functional Collaboration

• - Work closely with BSAs, Solution Architects, Integration Engineers, QA, and business SMEs to support testing, mock conversions, cutover planning, and hypercare activities.
• - Track open issues, risks, assumptions, dependencies, and status updates for assigned scope; escalate blockers early and communicate clearly with affected stakeholders.
• - Coordinate any offline migration activities for the assigned workstream, including file preparation, validation, handoff timing, and business communications.
• - Support UAT and dress-rehearsal cycles by validating data outcomes, tracing defects, documenting findings, and confirming remediation steps.

Knowledge Transfer & Capability Building

• - Document SQL logic, mapping assumptions, transformation rules, issue resolutions, and repeatable procedures so that future waves can reuse proven approaches.
• - Create and maintain training aids, runbooks, and reference materials for recurring extraction, mapping, validation, and offline migration tasks.
• - Build working familiarity with D365 data entities, data projects/packages, staging concepts, and Power Platform components relevant to reporting, workflow, and integration.
• - Contribute lessons learned after test cycles and deployments to strengthen the program’s internal data-migration capability over time.