About the Company
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe.
Responsibilities
- Design and develop ETL pipelines using Databricks SQL and Python / PySpark to enhance reporting, automate journal entries, and transform core financial processes.
- Architect, build, and own the most complex finance data pipelines in the Finance data lake using Databricks Jobs and Lakeflow Declarative Pipelines.
- Lead the technical design of AI use cases for the Finance and Accounting organisation.
- Build and maintain internal Finance applications (Databricks Apps, Genie Agents, 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 modelling conventions, documentation practices, and testing frameworks.
- Enforce and evolve Git-based version control, pull-request review processes, and CI/CD pipelines.
- Lead technical scoping and solutioning for requirements from Accounting, FP&A, Internal Audit, and Procurement teams.
- Serve as the primary technical point of contact during financial close.
- Partner with IT and Engineering on new system integrations.
- Mentor junior and mid-level engineers.
- Proactively identify architectural debt, performance bottlenecks, and tooling gaps.
Requirements
- 12+ years of experience in data engineering, analytics engineering, or finance systems.
- Deep proficiency in SQL and Python; hands-on experience with Apache Spark and the Databricks platform.
- Experience building and maintaining ELT/ETL pipelines from financial source systems (NetSuite, Salesforce, Stripe, Zuora, or similar).
- Strong understanding of core finance and accounting concepts.
- Ability to independently translate ambiguous Finance requirements into well-architected solutions.
- Comfortable driving technical conversations with both 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.
- Nice to have: Prior 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 DataLake pipelines, CPA, CFA, or formal finance/accounting background.