Finance Data Architect

Summary Finance at Q2 operates on enterprise data that lives across a complex, multi‑system landscape — Snowflake and beyond. This role exists because that data is not yet consistently usable. The Finance Data Architect closes that gap by owning two interconnected capabilities: building and governing finance‑ready semantic models and curated datasets drawn from Q2's full data estate, and authoring the AI workflow infrastructure — skills files, agent prompts, MCP context layers, and documentation — that allows Finance to execute complex, recurring processes repeatably and at scale. This is a builder role, not a consumer role. The right candidate has done this work before: translating messy, distributed enterprise data into trusted, finance‑ready outputs, and standing up agentic workflow patterns that hold up under real business conditions. The role sits within Finance and partners closely with Data/Architecture, Enterprise Solutions, and AI Enablement functions across Q2. Responsibilities Map, connect, and rationalize Finance‑relevant data across Q2's full data estate — Snowflake and distributed upstream sources — establishing canonical source alignment and lineage documentation for each Finance domain. Design and maintain curated datasets purpose‑built for Finance consumption: expense forecasting inputs, revenue and COGS drivers, headcount and compensation, and other key reporting and planning inputs. Partner with FP&A, Accounting, and FinOps stakeholders to define semantic models that encode metric definitions, dimensionality, calculation logic, and source‑of‑truth alignment in a form downstream systems and AI agents can reliably consume. Establish and drive adherence of naming standards, data quality checks, refresh cadences, and model documentation as part of a Finance semantic layer contract. Build lightweight validation and reconciliation processes that drive trust and adoption across Finance data consumers. Build trust through auditability of modeled data. Own the Finance MCP layer: design and maintain the context, definitions, guardrails, and grounding structures that enable AI agents to operate accurately within Finance workflows. Author and version markdown‑based skills, agent prompts, and workflow files that operationalize recurring Finance tasks — variance narratives, forecast driver updates, close support analyses, executive dashboard refresh, earnings narrative updates, and others as the library grows. Create and maintain a Finance AI artifact library: reusable prompts, golden examples, known failure modes, troubleshooting guidance, and acceptance criteria. Establish versioning standards and metadata practices (ownership, approval status, context dependencies) for all Finance AI artifacts. Partner with enterprise AI Enablement teams to ensure agents and tools are grounded in approved semantic definitions and operate within Finance governance guardrails. Serve as the connective layer between Finance and Q2's enterprise data ecosystem; align with Data/Architecture and Enterprise Solutions on upstream transformations, governance standards, and canonical source decisions. Drive adoption through documentation, demos, and stakeholder enablement — translating technical outputs into Finance‑accessible language and practice. Identify and surface process improvement and automation opportunities across Finance workflows, bringing forward use cases grounded in data and feasibility. Operate with a flexible mindset in ambiguous environments while continuing to move teams forward. Continuously learn and evolve as applied technologies mature and new technologies arise. Experience and Knowledge Required: Bachelor’s degree in Finance, Accounting, Analytics, Information Systems, or related field plus 5–7 years of relevant experience; advanced degree with 3–5 years; or equivalent demonstrated experience. Proven ability to navigate and rationalize distributed enterprise data environments — not just Snowflake‑native work, but connecting and harmonizing data across multiple source systems. Strong SQL capability and hands‑on experience working in Snowflake or equivalent cloud data warehouse environments. Demonstrated experience building semantic models, curated datasets, or data layer contracts that translate raw enterprise data into business‑facing outputs. Demonstrated ability to design and structure AI workflow infrastructure: including building prompt libraries, authoring agent skills or context files, or structuring MCP / retrieval‑grounding layers OR a proven track record of rapidly acquiring and applying emerging technical capabilities in a production environment. Exceptional written communication and documentation skills, including the ability to write for both technical and non‑technical audiences. Proven cross‑functional influence as an individual contributor — earns trust through technical credibility and clear communication, not organizational authority. Preferred: Finance domain depth in FP&A, expense forecasting, or revenue modeling in a SaaS or public‑company environment. Familiarity with enterprise planning and reporting tools (Anaplan, Power BI, Tableau) and experience designing semantic layers that feed them accurately. Experience building internal documentation systems, playbooks, or knowledge bases in a markdown‑first environment. Exposure to AI evaluation frameworks: prompt quality assessment, hallucination reduction patterns, agent guardrail design, or output validation. Comfort operating in an environment where the tooling is established but the patterns are still being built — a builder’s orientation, not an implementer’s. Fluent written and oral communication in English. Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time. Benefits Health & Wellness: Hybrid Work Opportunities, Flexible Time Off, Career Development & Mentoring Programs, competitive health insurance offerings, generous paid parental leave for eligible new parents. Community Volunteering & Company Philanthropy Programs. Employee Peer Recognition Programs – “You Earned it”. We are an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, genetic information, or veteran status. Applicants in California or Washington State may not be exempt from federal and state overtime requirements. #J-18808-Ljbffr Q2 India