Senior Analyst, Data Modernization & Intelligence (GenAI & Data Lifecycle Focus)

Deloitte•Tampa, FL

4d•Onsite

About The Position

This role sits at the intersection of GenAI enablement, data governance, and enterprise M365 platform delivery, supporting global, multi-tenant deployments. The Senior Analyst is responsible for testing, validating, and operationalizing AI-driven capabilities (Microsoft 365 Copilot, Gemini Enterprise, Claude) while ensuring alignment with data lifecycle management standards and governance controls.

Requirements

Hands-on experience with GenAI tools and platforms, including exposure to enterprise AI capabilities.
Strong understanding of data lifecycle management concepts, including data ingestion, processing, storage, access, and retention.
Experience with data validation, testing, and quality assurance in enterprise environments.
Working knowledge of data governance concepts, including classification, sensitivity, and compliance considerations.
Ability to analyze AI-driven outputs and system behaviors, identify inconsistencies, and escalate findings clearly.
Experience supporting controlled testing, defect management, and issue tracking workflows.
Strong problem-solving skills with the ability to operate in ambiguous, evolving technology environments.

Nice To Haves

Experience with Microsoft Purview (data governance, compliance, or information protection capabilities).
Exposure to multi-tenant or global enterprise environments.
Experience supporting AI/ML feature rollout, testing, or evaluation at scale.
Scripting or automation experience to support testing or validation workflows.
Familiarity with emerging AI tooling (prompt-based systems, AI agents, evaluation frameworks, etc.).
Experience translating technical findings into clear, governance-aligned documentation or guidance.

Responsibilities

Support the testing, validation, and rollout of GenAI capabilities, including Microsoft 365 Copilot, Gemini, and Claude, and related features across collaboration workloads.
Evaluate how AI features interact with enterprise data environments, ensuring alignment with data handling, retention, and classification requirements.
Execute end-to-end data lifecycle validation, including data ingestion, transformation, storage, access, and output behaviors within M365 and connected systems.
Partner with engineering, governance, and platform teams to identify risks, gaps, and inconsistencies in data usage across AI-enabled scenarios.
Contribute to controlled testing frameworks, including scenario-based validation, defect tracking, and repeatable test design.
Support the development of technical documentation, SOPs, and governance-aligned guidance for AI-enabled capabilities.
Provide technical troubleshooting and analysis for issues related to AI feature behavior, data inconsistencies, and platform integration.
Perform targeted analysis and reporting to support decision-making, with emphasis on data integrity and trend validation rather than standalone reporting deliverables.