Technical Business Analyst

OVERVIEW:

At Fortis, we lead the way in next generation payment technologies and solutions. We transform payments into a competitive advantage for our clients and partners, enabling businesses to reach uncharted growth and scale. As the solution of choice for the future of payments, Fortis moves payments closer to invisible with a proprietary platform that supports and strengthens the payments capabilities of merchants and software partners. We are a collaborative team of innovators, problem solvers, and builders, committed to the growth of our clients, partners, and team members. Through award winning software integrations, robust data, and industry vertical and commerce expertise, we deliver the ultimate frictionless commerce experiences. We are in hyper growth mode and seeking talented, innovative, and collaborative problem solvers to help us build and scale the future of payments. Grow your career with us and be on the cutting edge of the rapidly expanding FinTech payments space.

The Technical Business Analyst, Data Solutions is a creative problem solver and a consultative, product-minded partner to the business and to the teams that build our data platform. Rather than simply capturing requirements, you help shape them — turning business intent into well-defined data and API solutions that Data Engineering and AI Engineering can build with confidence — and you leverage AI-enabled tools for requirements development, business process development, data mapping, and troubleshooting and triage, validating what they produce.

Reporting to the Director, Data Solutions, you contribute to team standards and to the data platform roadmap and its change activities, which the Director owns, partnering closely with Agile Delivery Managers, Data Engineering, AI Engineering, and QA across AI and non-AI initiatives.

Business Partnership & Discovery

• Partner with business stakeholders on goals, constraints, and success criteria, proposing solution options and tradeoffs before requirements are finalized
• Facilitate discovery and design sessions as a subject matter expert in business processes and data, surfacing risks, dependencies, and downstream impact early
• Contribute to roadmap planning with Product Management, supporting the Director, Data Solutions (roadmap owner), and coordinate change activities — impacts, dependencies, communication, and readiness — for your initiative

Analysis & Solution Design

• Document requirements for data processes, platform capabilities, and APIs, translating business goals into user stories and functional, non-functional (e.g., performance, security, data quality, retention, auditability), and technical specifications with testable acceptance criteria
• Leverage AI-enabled tools to accelerate requirements development and business process documentation (current- and future-state flows), owning the accuracy, completeness, and traceability of the output
• Perform exploratory data analysis and collaborate with business and technical teams to inform design, including data modeling and schema design, guided by the Director, Data Solutions
• Develop data mappings (source-to-target, transformation rules, definitions) with AI-enabled tools, with human review before handoff to engineering
• Identify data quality, lineage, and availability needs, including data readiness for AI and analytics use cases

Agile Delivery & Execution

• Author and refine user stories, acceptance criteria, and specifications, partnering with the Agile Delivery Manager and Product Management to keep the backlog ready for planning
• Participate in Scrum ceremonies led by the Agile Delivery Manager, providing scope, dependency, and readiness input and flagging risks early
• Maintain traceability from business intent through release, working in line with the AI Development Life Cycle (AIDLC) where applicable

Quality, Validation & Troubleshooting

• Validate acceptance criteria and delivered work against business intent and data accuracy, supporting UAT, release planning, and post-deployment validation
• Validate AI-assisted output for accuracy, completeness, and sensitive-data handling, per company policies on data security and responsible AI use
• Leverage AI-enabled tools to troubleshoot and triage data and platform issues — analyzing discrepancies and isolating likely root causes — partnering with Data Engineering and Agile Delivery Managers on resolution

Documentation, Standards & Continuous Improvement

• Maintain current documentation (requirements, data definitions, mappings, diagrams) and help evolve TBA standards, templates, and AI-enabled practices to shorten turnaround to delivery