Senior Manager, Finance Data and AI

As Senior Manager, Finance Data and AI, you will lead the team that owns the data foundations, finance semantic layer, financial reporting, and AI-enabled analytics that power Databricks' Finance and Accounting organization. You will report to the Senior Director, Finance Data, AI & Strategy, and serve as the domain and technical anchor for a team that turns financial operations into trusted, well-governed data and reporting. This individual is expected to be based in Bengaluru.

This is a high-impact role at the intersection of finance and accounting domain expertise and modern BI/analytics capability. It is less about deep distributed-systems engineering, and more about deeply understanding how Finance and Accounting operate (close, reconciliations, revenue recognition, chart of accounts) and building a trusted data foundations on top of the Databricks platform and Finance DataLake that Finance and Accounting can rely on every day.

• Orchestrate jobs using Databricks Jobs and Lakeflow Declarative Pipelines, with built-in data validation and reconciliations, to ensure Finance and Accounting can trust the data behind every report
• Own and evolve the Finance semantic layer: metric definitions, business logic, and data models that ensure a single source of truth for financial reporting across Finance, Accounting, and the broader business
• Partner closely with Accounting during month-end and quarter-end close, providing hands-on support to ensure reporting data is accurate, timely, and reconciled, and driving timely resolution of data-related issues
• Build and maintain dashboards and reporting for monthly, quarterly, and executive-level reporting, translating financial data into decision-ready insight for Finance leadership and the CFO organization
• Identify, scope, and deliver AI use cases that materially change how Finance and Accounting work day to day, including forecasting automation, anomaly detection, and natural language interfaces (Genie Spaces) to financial data
• Build and maintain internal Finance applications (Databricks Apps, Genie Spaces, dashboards) that enable self-service analytics for non-technical Finance and Accounting stakeholders
• Publish curated, well-documented finance datasets and metrics, enforcing row-level security and data access policies appropriate for financial data
• Partner with Accounting, FP&A, Internal Audit, and Procurement to deeply understand business and reporting requirements, and translate them into scalable semantic models and analytics products within the Finance DataLake
• Manage and grow a team of finance data analysts / finance engineers, setting standards for semantic modeling, dashboard design, and analytics delivery, reviewing work, and developing talent
• Enforce Git-based version control, change management, and CI/CD practices to satisfy SOX change management requirements for reporting and semantic layer changes
• Partner with IT and Engineering to provide requirements and perform UAT for new systems and processes affecting Finance data and reporting
• Establish data management, semantic modeling, and documentation standards and best practices for the Finance organization
• Serve as a proactive leader who regularly assesses Finance and Accounting pain points, aligns with cross-functional teams on organizational objectives, and holds the team accountable for high-quality, business-relevant results

What We Look For:

• 12+ years of experience in business intelligence, financial analytics, or analytics engineering, with deep exposure to finance/accounting operations, and at least 3 years in a people management or team lead capacity
• Strong understanding of core finance and accounting concepts (month-end/quarter-end close, revenue recognition, intercompany, chart of accounts, and financial reporting) and the ability to translate them into semantic models and metrics
• Proficiency in SQL and Python
• Experience with BI and data visualization tooling (Tableau, Looker, Power BI, or Databricks AI/BI dashboards), with a track record of building Finance-facing dashboards and self-service reporting products
• Familiarity with ELT/ETL concepts and how financial source systems (SAP, Salesforce, Stripe, Zuora, or similar) feed into a centralized data lake; direct pipeline-building experience is a plus, not a requirement
• Demonstrated ability to translate ambiguous Finance requirements into well-scoped, well-governed reporting and analytics deliverables
• Comfortable working across both technical (Engineering, Data Platform) and non-technical (Accounting, FP&A) stakeholders, translating data concepts for a financial audience and financial concepts for a technical audience
• Familiarity with AI/ML concepts and enthusiasm for applying them to Finance and Accounting workflows