Revenue Business Analyst/Functional Lead

CGI•Dallas, TX

2d•Hybrid

About The Position

We're growing rapidly and are looking for a Revenue BA/Functional Lead responsible for Revenue domain discovery, requirements, business definitions, business rule documentation, source to target functional mappings, metric definitions, Finance engagement, requirements traceability, reconciliation, and business UAT for the Revenue Enterprise Data Product. We're a close knit team that has access to global resources. You'll have the opportunity to explore a wide range of industries, technologies, and geographies, all while enjoying the personal touch that our local operating approach offers. Growth at CGI is driven by your goals, so if you're looking for an inclusive place where you're empowered to chart your own path, then we'd love to meet you. This position is located in our Plano, Texas office with work performed at client site in Dallas, Texas. For the first 6 weeks, daily onsite presence is a requirement and from there a hybrid working model will be acceptable with onsite presence just north of the DFW airport.

Requirements

Working knowledge of analytical data models, data quality, governed metrics, semantic layers, and enterprise Data Product concepts strongly preferred.
Strong workshop facilitation, stakeholder management, documentation, decision facilitation, and business acceptance experience required.
Experience translating complex revenue/financial concepts into implementable data rules, and experience investigating and resolving data reconciliation variances.
Business Analysis
Communication
Finance
Stakeholder management
Workshop Facilitation
Data Modeling

Responsibilities

Serves as the primary functional bridge between the client's Finance and domain stakeholders and CGI architecture, data engineering, governance, BI, and QA teams.
Must demonstrate strong data oriented business analysis capabilities, experience translating complex revenue/financial concepts into implementable data rules, and experience investigating and resolving data reconciliation variances.