GAQ327R290

As a tax data & technology leader you will architect the redesign of our tax processes by building automation solutions and managing finance data pipelines that power our global tax organization. You will report to the Senior Director, Tax and serve as the technical anchor between the tax team and the finance data team. You will enable us to reimagine the tax function by leveraging our finance data lake to improve accuracy and efficiency of our tax processes and enable new functionality in reporting and forecasting. Importantly, you will be responsible for bridging the gap between our team's subject matter experts, our technology solutions, and all of the business data needed to support the increasing data requirements for global tax reports.

This is a high-impact role that will build purposeful, reliable solutions on top of the Databricks platform and Finance Datalake to accelerate global Tax.

The impact you will have:

• Orchestrate jobs using Databricks Jobs and Lakeflow Declarative Pipelines with built-in data validation and reconciliations that improve tax deliverables via speed & accuracy
• Identify, scope, and deliver AI use cases for Tax, including tax calculation automation, anomaly detection, and natural language interfaces to the financial data that supports tax
• Build and maintain internal tax applications (Databricks Apps, Genie Spaces, dashboards) that enable self-service for non-technical Finance stakeholders
• Build reports and dashboards for monthly, quarterly, and executive-level reporting
• Ensure data integrations are maintained and reconciled to support tax reporting & forecasting use cases
• Create & maintain tax calculation automations & reports are up to date (teaming with tax colleagues), accurate, and reviewable for internal and external stakeholders (e.g. external auditors)
• Enforce Git-based version control, pull-request reviews, and CI/CD pipelines (Declarative Automation Bundles, GitHub Actions) to satisfy SOX change management requirements
• Provide support during tax close and ensure timely resolution of data-related issues
• Partner with IT and Engineering to provide requirements and perform UAT of new systems and processes that interact with tax
• Establish coding, data management, and documentation standards and best practices

What we look for:

• 6+ years of experience in tax automation, transformation, or data engineering, with at least 2 years in a tax or tax adjacent field
• Experience in SQL and Python for data pipeline development; experience with the Databricks platform is a strong plus
• Hands-on experience building and maintaining ELT/ETL pipelines connecting tax source systems (Netsuite, Salesforce, Stripe, SAP, or similar) to tax automation tools OR from those source systems into tax workflows and reports
• Understanding of core tax and accounting concepts including close processes, tax provision, intercompany accounting, tax compliance, and financial reporting
• Demonstrated ability to translate ambiguous Tax requirements into well-scoped, maintainable technical deliverables
• Comfortable working across both technical (Finance Data Team) and non-technical (Tax, Accounting, FP&A) stakeholders
• Experience with BI and data visualization tooling; ability to build Tax-facing dashboards and self-service products
• Familiarity with AI/ML concepts and enthusiasm for applying them to Tax workflows

Nice to Have

• Prior experience at a high-growth SaaS or cloud infrastructure company
• Exposure to AI/BI tools, Genie, or LLM-powered applications
• Experience with Declarative Automation Bundles or CI/CD for Finance DataLake pipelines
• CPA, CFA, or formal finance/accounting background

Why This Role

You will be embedded in a Tax organization that takes data and AI seriously, reporting directly to the Senior Director of Tax, with visibility to CAO-level priorities. The team operates with engineering rigor and tax accountability, and you will have the autonomy to define how we reimagine the tax function at Databricks and develop use cases that may expand to our customers.