Sr Business Data Analyst

Functional Data Analyst

Location: Frisco, TX

Job type: Full time

Role Overview

As a client-facing

Functional Data Analyst

, you will serve as the critical strategic bridge connecting business stakeholders, customer outcomes, and technical engineering teams. You will drive data modernization, migration, advanced analytics, and cutting-edge AI-enabled initiatives. Operating at the intersection of business strategy and data execution, you will transform complex operational challenges into highly structured, testable functional specifications.

Core Responsibilities

• Business Architecture & Discovery:

Lead discovery sessions with clients to map business processes, identify data gaps, and translate complex requirements into actionable user stories, KPIs, and acceptance criteria.

• Data Product Strategy & AI Innovation:

Define functional blueprints for next-generation data products and AI/ML use cases, assessing feasibility, business value, and data readiness.

• Technical Solution Design:

Partner with Enterprise Architects to design data models, verify logical data structures, and create comprehensive source-to-target mappings, ensuring alignments with long-term customer goals.

• Data Governance & Integrity:

Champion data health by defining data dictionaries, access rules, lineage tracking, business glossaries, and strict data-quality controls.

• Analytics, Validation, & UAT:

Write complex SQL queries to profile and troubleshoot data, build functional test scenarios, execute pre/post-migration data reconciliation, and orchestrate final User Acceptance Testing (UAT) with clients.

What We Are Looking For

• The Bridge:

A professional who can sit across from a corporate client, understand their business rules, and then write the SQL queries and functional data models to make it happen.

• Technical Toolkit:

Practical, hands-on experience with SQL querying, source-to-target data mapping, ERDs, and data profiling.

• Forward-Looking Mindset:

Familiarity with data governance rules, data-product life cycles, and validating AI/ML insights from a business perspective.