Director, FP&A Digitization (R5465)

We’re looking for a Director of FP&A Digitization to accelerate Finance’s transformation through modern data architecture, automation, and enterprise AI. This leader will sit at the intersection of Finance, Engineering, and Product—owning the platforms, data foundations, and AI capabilities that future‑proof how FP&A plans, forecasts, and drives decisions across the company.

This role is ideal for someone who blends financial acumen with technical depth, enjoys building from zero‑to‑one, and thrives in a fast‑moving, iterative environment.

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.

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.

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.

Drive MDM strategy for critical Finance domains. Maintain high‑accuracy data environments that underpin forecasting, product analytics, revenue modeling, and enterprise reporting.

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.

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.

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.

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.

You think in systems—architecting scalable foundations rather than one‑off tools.

You a strong track record of implementing scalable best practices.

You communicate simply around complex concepts and build trust through transparency and data quality.

You’re iterative: ship fast, learn fast, and refine with users.

You enjoy solving ambiguous, cross‑functional problems with a product mindset.

You elevate Finance by making technology accessible, reliable, and impactful for every user.

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, Tableau, Anaplan, SAP S/4, and modern data governance tools.

Education: M.S. Information & Data Science

Core Expertise:

Finance AI Strategy & Deployment · Generative BI & Text-to-SQL · RAG Application Development · Document

Intelligence · Semantic Data Modeling · Financial Systems Transformation · Master Data Management · Data Governance & Lineage · GenAI Product Ownership · Executive Stakeholder Management

Platforms & Tools: 

Databricks or Snowflake

AI & LLMs: Snowflake Cortex Code · Claude Code · RAG Pipelines · Document Intelligence 

Data & Analytics: Snowflake · Databricks · ThoughtSpot · Tableau · Collibra 

Planning & Finance Systems: Anaplan · SAP S/4 · Hyperion · SFDC 

Languages & Dev: SQL (Advanced) · Python (Intermediate) 

Delivery & Operations: JIRA · ServiceNow · Tableau