Senior Manager, Finance Data and AI
Databricks
| Company | Databricks |
| Category | Data & Analytics |
| Location | Bengaluru |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Manager |
| Salary | Not stated by the employer |
| Posted | 1 Jul 2026 |
| Last verified | 11 Aug 2026 |
| Source | Employer ATS (greenhouse) |
Description
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 infrastructur