<p data-pm-slice="1 1 []"><strong>GAQ426R192</strong></p> <p><strong>About the Role</strong></p> <p>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.</p> <p>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.</p> <p><strong>What You Will Do:</strong></p> <ul> <li>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</li> <li>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</li> <li>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</li> <li>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</li> <li>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</li> <li>Build and maintain internal Finance applications (Databricks Apps, Genie Spaces, dashboards) that enable self-service analytics for non-technical Finance and Accounting stakeholders</li> <li>Publish curated, well-documented finance datasets and metrics, enforcing row-level security and data access policies appropriate for financial data</li> <li>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</li> <li>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</li> <li>Enforce Git-based version control, change management, and CI/CD practices to satisfy SOX change management requirements for reporting and semantic layer changes</li> <li>Partner with IT and Engineering to provide requirements and perform UAT for new systems and processes affecting Finance data and reporting</li> <li>Establish data management, semantic modeling, and documentation standards and best practices for the Finance organization</li> <li>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</li> </ul> <p><strong>What We Look For:</strong></p> <ul> <li>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</li> <li>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</li> <li>Proficiency in SQL and Python</li> <li>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</li> <li>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</li> <li>Demonstrated ability to translate ambiguous Finance requirements into well-scoped, well-governed reporting and analytics deliverables</li> <li>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</li> <li>Familiarity with AI/ML concepts and enthusiasm for applying them to Finance and Accounting workflows</li> </ul> <p><strong>Nice to Have:</strong></p> <ul> <li>Prior experience at a high-growth SaaS or cloud infrastructure company</li> <li>Exposure to AI/BI tools, Genie, or LLM-powered applications</li> <li>Experience with Declarative Automation Bundles or CI/CD for Finance DataLake pipelines</li> <li>CPA, CFA, or formal finance/accounting background</li> </ul> <p&