# Director, FP&A Digitization

**Company:** [Shield AI](https://hotfix.jobs/companies/shield-ai)
**Location:** San Francisco, CA
**Role:** Revenue Operations
**Salary:** $200k – $300k/yr
**Experience:** 12+ years
**Skills:** SQL, Python, Snowflake, Databricks, thoughtspot, Tableau, anaplan, sap s/4, RAG, Generative AI, Data Governance, semantic data modeling, master data management, collibra, Jira
**Posted:** 2026-07-31

> Lead Finance AI strategy, data architecture, and product ownership to modernize FP&A through generative AI, semantic layers, RAG, and systems transformations. Requires 12+ years experience, technical depth in data/AI platforms, and cross-functional leadership blending finance, product, and engineering.

## 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, 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

## How you work
- Think in systems—architecting scalable foundations rather than one-off tools.
- Strong track record of implementing scalable best practices.
- Communicate simply around complex concepts and build trust through transparency and data quality.
- Iterative: ship fast, learn fast, and refine with users.
- Enjoy solving ambiguous, cross-functional problems with a product mindset.
- Elevate Finance by making technology accessible, reliable, and impactful for every user.

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