Job Opportunities API

About Goods & Services    Goods & Services is a product design and engineering company.  We solve mission-critical challenges for some of the world’s largest enterprises, with deep expertise in highly regulated industries—including life sciences and financial services . Our design-led approach allows us to apply cutting-edge capabilities in AI, Data and Hardware Engineering to companies of any size.  Headquartered in the United States , we operate regional development centers in Mexico and the United Kingdom . This global footprint—anchored by our nearshore model—enables us to deliver at scale with the speed, efficiency, and cultural alignment our clients expect. About the job    Goods & Services is looking for a Finance Product Owner – Data & Accounting who serves as the primary functional bridge between US Finance/Accounting leadership and the Data Engineering team. This role transforms accounting logic, general ledger feeds, and financial reconciliation workflows into actionable data models and technical backlogs. What you’ll do: Partner directly with US Finance and Accounting executives to capture, prioritize, and structure business processes, regulatory requirements, and reporting objectives. Collaborate with Data Engineers to translate general ledger feeds, accounting sub-ledgers, and complex reconciliation logic into data models, technical user stories, and acceptance criteria. Own, groom, and prioritize the finance data backlog. Guide sprint refinement sessions and lead User Acceptance Testing (UAT) alongside accounting stakeholders. Maintain real-time operational alignment with US financial leadership to ensure data platform delivery meets strict corporate finance and auditing standards. What you’ll need: 5+ years of experience as a Product Owner or Senior Financial Systems Analyst interfacing with Data/Engineering teams. Strong functional knowledge of US GAAP, General Ledger (GL) systems, sub-ledger reconciliation, and financial reporting. Hands-on experience structuring user stories for Data Engineering/ETL teams.