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
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on Twitter, LinkedIn and Facebook.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
Skills Required
- 15+ years of experience in data engineering, finance systems, or analytics engineering
- At least 5 years in a people management or team lead capacity
- Proficiency in SQL for data pipeline development
- Proficiency in Python for data pipeline development
- Hands-on experience building and maintaining ELT/ETL pipelines connecting financial source systems (NetSuite, Salesforce, Stripe, Zuora, or similar)
- Understanding of core finance and accounting concepts (close processes, revenue recognition, intercompany, chart of accounts, reporting)
- Experience building Finance-facing dashboards and self-service BI/data visualization products
- Experience enforcing Git-based version control, pull-request reviews, and CI/CD (GitHub Actions) to meet SOX/change management requirements
- Comfort working across technical and non-technical stakeholders (Accounting, FP&A, Internal Audit, Procurement)
- Familiarity with AI/ML concepts and enthusiasm for applying them to Finance workflows (forecasting automation, anomaly detection, natural language interfaces)
- Experience with Apache Spark or the Databricks platform
- Prior experience at a high-growth SaaS or cloud infrastructure company
- Exposure to Genie, LLM-powered applications, or other AI/BI tools
- Experience with Declarative Automation Bundles or CI/CD for Finance DataLake pipelines
- CPA, CFA, or formal finance/accounting background
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
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Equity Value & Accessibility — Equity grants and RSUs are a major part of total compensation and are highlighted for meaningful upside potential. Stock-based awards and refreshers contribute to strong overall pay positioning across senior technical and go-to-market roles.
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Healthcare Strength — Medical, dental, and vision coverage are complemented by mental-health resources, an EAP, and wellness reimbursements. Health benefits are consistently framed as comprehensive and competitive.
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Parental & Family Support — Paid parental leave for all parents, fertility support, and backup care options provide tangible assistance for family needs. Hybrid work norms and team-day structure further ease coordination for caregivers.
Databricks Insights
What We Do
As the leader in Unified Data Analytics, Databricks helps organizations make all their data ready for analytics, empower data science and data-driven decisions across the organization, and rapidly adopt machine learning to outpace the competition. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
