Senior Finance Data and AI Specialist

Responsibilities

• Develop and maintain ETL pipelines using Databricks Lakehouse and Python/PySpark to enhance reporting, automate journal entries, and transform finance processes across accounting and FP&A domains, including revenue, expenses, equity, commissions, and tax.
• Build and maintain finance data pipelines in the Finance data lake using Databricks Jobs and Lakeflow Spark Declarative Pipelines, including data validation and reconciliation logic.
• Develop and iterate on AI-assisted tools for Finance and Accounting, including workflow automation, anomaly detection, and reporting enhancements.
• Contribute to Finance applications, including Databricks Apps, Genie Spaces, and AI/BI dashboards, enabling self-service analytics.
• Build and maintain reports and dashboards for monthly, quarterly, and executive-level reporting.
• Support row-level security and data access policies across Finance DataLake datasets.
• Gather requirements from Accounting, FP&A, Internal Audit, and Procurement teams and deliver well-documented technical solutions.
• Follow Git-based version control, pull-request review, and CI/CD processes, including Declarative Automation Bundles and GitHub Actions, to meet SOX change-management requirements.
• Support financial close by monitoring pipelines, investigating data issues, and escalating as needed.
• Participate in UAT for system integrations and assist with technical documentation.
• Contribute to coding standards and data-modeling conventions.

Requirements

• 7+ years of experience in finance and accounting, data engineering, analytics engineering, or finance systems.
• Proficiency in SQL and Python for pipeline development.
• Experience with Apache Spark or the Databricks platform is a strong plus.
• Experience connecting to and ingesting data from financial source systems such as SAP, NetSuite, Salesforce, Stripe, or Zuora.
• Working knowledge of finance and accounting concepts, including close processes, revenue recognition, and financial reporting.
• Ability to translate Finance requirements into clean, maintainable technical solutions.
• Comfortable communicating with technical and non-technical audiences.
• Experience contributing to BI dashboards and self-service data products.
• Curiosity about AI/ML and interest in applying new techniques to Finance workflows.

Nice to Have

• Experience at a high-growth SaaS or cloud infrastructure company.
• Exposure to AI/BI tools, Genie One, or LLM-powered applications.