Director, FP&A Digitization (R5465)

Job Description:

What you'll do:

Finance AI Strategy & Roadmap
Define and execute the AI strategy for FP&A, converting generative BI, text‑to‑SQL, RAG, and document intelligence into real business impact. Identify the highest‑value use cases and turn proof‑of‑concepts into scaled, production‑ready tools.
Product Ownership for Finance Technology
Own Finance’s AI & data products end‑to‑end—requirements, UX/UI, testing, release cadence, and roadmap. Build enterprise document intelligence platforms and semantic data services that enable Finance to operate with speed, automation, and confidence.
Modern Data Architecture for Finance
Lead the design and governance of the semantic layer that allows LLMs and BI tools to safely interact with financial data. Ensure accuracy, lineage, and business‑logic integrity across thousands of data objects.
Master Data Management & Quality
Drive MDM strategy for critical Finance domains. Maintain high‑accuracy data environments that underpin forecasting, product analytics, revenue modeling, and enterprise reporting.
Finance Systems Modernization
Partner with FP&A leadership to modernize planning, reporting, and modeling systems. Lead platform migrations on behalf of FP&A (e.g., Costpoint  →  Oracle or Vena → Anaplan), streamline workflows, and drive adoption across large user communities.
Analytics & AI Program Leadership
Run a cross‑functional delivery engine across Finance, Accounting, IT, and PX and Rev Ops.  Manage intake, prioritization, and execution for a portfolio of analytics and AI initiatives—balancing innovation with operational reliability.
Enterprise Data Governance
Chair Finance’s Data Governance Council, establishing standards for quality, definitions, access, and usage. Create the trust framework that enables Finance to proactively manage systems and data changes without interrupting key data workflows and adopt AI safely at scale.
Team Leadership & Development
Build and scale high‑performing technical Finance teams—including data engineering, analytics, systems, and AI product contributors. Shape operating rhythm, delivery processes, and long‑term capability development.

Required qualifications:

12+ years in Finance technology, FP&A systems, data engineering, analytics, or AI—preferably in tech or high‑growth environments.
Strong experience building and deploying generative AI solutions, RAG pipelines, semantic layers, and data governance frameworks.
Proven ability to translate Finance problems into technical architectures and production‑grade products.
Track record of leading cross‑functional teams (10–20+ people) and overseeing multi‑million‑dollar portfolios.
Comfortable operating as a hybrid Finance + Product + Data leader.
Executive‑level communication skills and experience presenting strategy to CFO‑staff.
Advanced SQL; working Python; hands‑on familiarity with Snowflake, Databricks, ThoughtSpot, T