Staff Data and AI Engineer, Finance

GAQ327R175

About the Role

This role is a part of the Finance Organisation.

As Finance Data Lead on the Finance Data and AI team, you will be the technical authority behind the data pipelines, AI systems, and internal applications that power Databricks' Finance and Accounting organization. You will report to the Senior Manager, Finance Data and AI and serve as the individual contributor who sets the technical bar, drives architectural decisions, and delivers the highest-complexity work on the team. This individual is expected to be based in Bengaluru.

This is a high-impact role at the intersection of finance domain expertise and data platform capability. You will work closely with a team of finance data engineers as a technical lead and mentor, and partner directly with Accounting, FP&A, and Finance leadership to define what gets built and how.

You will be embedded in a Finance organization that takes data and AI seriously, with visibility to CFO-level priorities. The team operates with engineering rigor and Finance accountability, and you will have the autonomy to define how the Finance DataLake and modern Finance data infrastructure should evolve at Databricks.

What You Will Do:

• Architect, build, and own the most complex finance data pipelines in the Finance DataLake, using Databricks Jobs and Lakeflow Declarative Pipelines with built-in data validation and reconciliations


• Lead the technical design of AI use cases for the Finance and Accounting organization, including forecasting automation, anomaly detection, and natural language interfaces to financial data


• Build and maintain internal Finance applications (Databricks Apps, Genie Spaces, dashboards) that enable self-service for non-technical Finance stakeholders


• Design and deliver curated Finance DataLake 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 across the Finance engineering team


• Enforce and evolve Git-based version control, pull-request review processes, and CI/CD pipelines (Declarative Automation Bundles, GitHub Actions) to satisfy SOX change management requirements


• 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, ensuring data accuracy and timely resolution of pipeline issues


• Partner with IT and Engineering on new system integrations, providing detailed technical requirements and leading UAT


• Mentor junior and mid-level engineers through code reviews, pairing, and design discussions, raising the technical quality of the broader team


• Proactively identify architectural debt, performance bottlenecks, and tooling gaps, and drive resolution with minimal direction

What We Look For:

• 12+ years of experience in data engineering, analytics engineering, or finance systems, with a track record of owning complex, production-grade pipelines end-to-end


• 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) into a centralized data lake


• Strong understanding of core finance and accounting concepts including close processes, revenue recognition, intercompany, chart of accounts, and financial reporting


• Ability to independently translate ambiguous Finance requirements into well-architected, maintainable technical 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 with demonstrated enthusiasm for applying them to Finance workflows

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