Data and AI Lead, Finance

Responsibilities

• Design and develop ETL pipelines using Databricks SQL and Python/PySpark to improve reporting, automate journal entries, and transform finance and accounting processes across revenue, expenses, equity, commissions, and tax.
• Architect, build, and own complex finance data pipelines in the finance data lake using Databricks Jobs and Lakeflow Declarative Pipelines, including data validation and reconciliations.
• Lead the technical design of AI use cases for Finance and Accounting, including forecasting automation, anomaly detection, and natural-language interfaces to financial data.
• Build and maintain internal finance applications, including Databricks Apps, Genie Agents, and AI/BI dashboards.
• Design and deliver curated finance datasets and enforce row-level security, data access policies, and Unity Catalog governance standards.
• Define and champion coding standards, data-modeling conventions, documentation practices, and testing frameworks.
• Manage Git-based version control, pull-request reviews, and CI/CD pipelines using Declarative Automation Bundles and GitHub Actions to satisfy SOX change-management requirements.
• Lead technical scoping and solutioning for Accounting, FP&A, Internal Audit, and Procurement requirements.
• Serve as the primary technical contact during financial close, ensuring data accuracy and timely resolution of pipeline issues.
• Partner with IT and Engineering on system integrations, providing technical requirements and leading user acceptance testing.
• Mentor junior and mid-level engineers through code reviews, pairing, and design discussions.
• Identify architectural debt, performance bottlenecks, and tooling gaps, and drive resolutions.

Requirements

• 12+ years of experience in data engineering, analytics engineering, or finance systems, with ownership of complex production-grade pipelines.
• Deep proficiency in SQL and Python, with hands-on experience using Apache Spark and Databricks.
• Experience building and maintaining ELT/ETL pipelines from financial source systems such as NetSuite, Salesforce, Stripe, or Zuora into a centralized data lake.
• Strong understanding of finance and accounting concepts, including close processes, revenue recognition, intercompany accounting, chart of accounts, and financial reporting.
• Ability to translate ambiguous Finance requirements into well-architected, maintainable technical solutions.
• Ability to lead technical discussions with engineering peers and non-technical Finance stakeholders.
• Experience building Finance-facing dashboards, self-service BI products, and executive reporting layers.
• Familiarity with AI/ML concepts and applying them to Finance workflows.

Nice to Have

• Experience at a high-growth SaaS or cloud infrastructure company.
• Hands-on experience with AI/BI tools, Genie, or LLM-powered applications.
• Experience with Declarative Automation Bundles or CI/CD for finance data lake pipelines.
• CPA, CFA, or formal finance/accounting background.