Drimva

Databricks

Tax Data & Technology Manager

$161K–$221K

San Francisco, California · Manager · Full-time · Posted Sep 14, 2026

Experience
6+ years in tax automation, transformation, or data engineering; at least 2 years in a tax or tax-adjacent field.

About the job

Leads tax process redesign by building automation, managing finance data pipelines, and developing reporting and AI solutions for the global tax organization.

What you'll do

  • Orchestrate and maintain data pipelines, integrations, validations, and reconciliations that support tax reporting and forecasting.
  • Build tax automations, applications, dashboards, and AI use cases for calculation, anomaly detection, and self-service access to financial data.
  • Establish engineering and data practices, support tax close, and partner with tax, finance, IT, and engineering stakeholders on systems and requirements.

What they ask for

  • 6+ years of experience in tax automation, transformation, or data engineering, including at least 2 years in a tax or tax-adjacent field.
  • SQL and Python experience for data pipeline development.
  • Hands-on experience building and maintaining ELT/ETL pipelines connecting tax source systems to tax automation tools, workflows, or reports.
  • Understanding of core tax and accounting concepts, including close processes, tax provision, intercompany accounting, tax compliance, and financial reporting.

Nice to have

  • Experience with the Databricks platform; familiarity with AI/ML concepts and applying them to tax workflows.
  • Prior experience at a high-growth SaaS or cloud infrastructure company; exposure to AI/BI tools, Genie, LLM-powered applications, Declarative Automation Bundles, CI/CD, or a CPA, CFA, or finance/accounting background.

Pay

$161,000 — $221,450 USD (salary range)

Tools

SQL, Python, Databricks Jobs, Lakeflow Declarative Pipelines, Databricks Apps, Genie Spaces, GitHub Actions, Declarative Automation Bundles

AI focus

Identify and deliver tax AI use cases, including tax calculation automation, anomaly detection, and natural-language interfaces to financial data.

Model-written summary · the original posting is authoritative

First seen Oct 10, 2026 · Last verified Nov 4, 2026 (UTC)