Senior Manager, Finance Data and AI

GAQ426R192

About the Role

As Senior Manager, Finance Data and AI, you will lead the design, development, and delivery of data pipelines, AI use cases, and internal applications that power Databricks' Finance and Accounting organization. You will report to the Senior Director, Finance Data, AI & Strategy, with visibility to CFO-level priorities, and serve as the technical anchor for a team that bridges financial operations and modern data engineering. 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 — less about writing distributed systems from scratch, and more about building purposeful, reliable solutions on top of the Databricks platform and Finance DataLake to accelerate Finance.

You will be embedded in a Finance organization that takes data and AI seriously. 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:

• Orchestrate jobs using Databricks Jobs and Lakeflow Declarative Pipelines with built-in data validation and reconciliations


• Identify, scope, and deliver 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


• Build reports and dashboards for monthly, quarterly, and executive-level reporting


• Publish curated finance datasets and enable self-service analytics, while enforcing row-level security and data access policies


• Partner with Accounting, FP&A, Internal Audit, and Procurement teams to understand business requirements and translate them into scalable technical solutions within the Finance DataLake


• Manage and grow a team of finance data engineers, setting technical standards, reviewing work, and developing talent


• 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 financial 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


• Establish coding, data management, and documentation standards and best practices


• Serve as a proactive leader who regularly assesses pain points, aligns with cross-functional teams on organizational objectives, and inspires and holds team members accountable for achieving high-quality results

What We Look For:

• 15+ years of experience in data engineering, finance systems, or analytics engineering, with at least 5 years in a people management or team lead capacity


• Proficiency in SQL and Python for data pipeline development; experience with Apache Spark or the Databricks platform is a strong plus


• Hands-on experience building and maintaining ELT/ETL pipelines connecting financial source systems (Netsuite, Salesforce, Stripe, Zuora, or similar) into a centralized data lake


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


• Demonstrated ability to translate ambiguous Finance requirements into well-scoped, maintainable technical deliverables


• Comfortable working across both technical (engineering, data platform) and non-technical (Accounting, FP&A) stakeholders


• Experience with BI and data visualization tooling; ability to build Finance-facing dashboards and self-service products


• Familiarity with AI/ML concepts and enthusiasm for applying them to Finance 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