Role at a glance
- Job function
-
AI & Data Data Engineering
- Salary
- Not Disclosed
- Location
- Bengaluru, India
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 12+ years of experience in data engineering, analytics engineering, or finance systems
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Role Summary
The Finance Data Lead is the technical authority and individual contributor for data pipelines, AI systems, and internal applications supporting Databricks' Finance and Accounting organisation. The role partners with Accounting, FP&A, Finance leadership, and other teams to shape technical solutions and lead complex engineering work.
What You'll Do
- Design and develop ETL pipelines for finance reporting, journal-entry automation, and accounting and FP&A processes.
- Architect and own complex finance data pipelines with validation and reconciliations.
- Lead technical design for Finance and Accounting AI use cases and build internal Finance applications and self-service tools.
- Deliver curated Finance datasets and enforce data access policies, row-level security, and Unity Catalog governance.
- Define engineering standards, data modelling conventions, documentation, testing, version control, and CI/CD practices.
- Lead technical scoping and integrations, support financial close, and mentor engineers.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
12+ years in data engineering, analytics engineering, or finance systems; deep proficiency in SQL and Python and hands-on Apache Spark and Databricks experience; experience building ETL/ELT pipelines from financial source systems into a centralized data lake; strong knowledge of finance and accounting concepts; ability to translate ambiguous Finance requirements into technical solutions and communicate with engineering and Finance stakeholders; experience building Finance-facing dashboards, self-service BI products, and executive reporting layers; familiarity with AI/ML concepts and applying them to Finance workflows.
Required
- Track record of owning complex, production-grade pipelines end-to-end.
- Experience building and maintaining ELT/ETL pipelines from financial source systems (NetSuite, Salesforce, Stripe, Zuora, or similar)...
- Strong understanding of core finance and accounting concepts, including close processes, revenue recognition, intercompany, chart of...
- Ability to independently translate ambiguous Finance requirements into well-architected, maintainable technical solutions.
- Comfortable driving technical conversations with both engineering peers and non-technical Finance stakeholders.
- Experience building Finance-facing dashboards, self-service BI products, and executive reporting layers.
- Familiarity with AI/ML concepts with demonstrated enthusiasm for applying them to Finance workflows.
Preferred
- Prior experience at a high-growth SaaS or cloud infrastructure company.
- Hands-on experience with 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.
Original job description
Content provided by the employer
Original job description
Content provided by the employer
GAQ327R175
About the Role
This role is a part of the Finance Organisation.
As Finance Data Lead on the Finance Data and AI team, you will be the technical authority behind the data pipelines, AI systems, and internal applications that power Databricks' Finance and Accounting organisation. You will report to the Senior Manager, Finance Data and AI and serve as the individual contributor who sets the technical bar, drives architectural decisions, and delivers the highest-complexity work on the team. 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. You will work closely with a team of finance data engineers as a technical lead and mentor, and partner directly with Accounting, FP&A, and Finance leadership to define what gets built and how.
What You Will Do:
- Design and develop ETL pipelines using Databricks SQL and Python / PySpark to enhance reporting, automate journal entries, and transform core financial processes across various domains in accounting and FP&A, such as revenue, expenses, equity, commissions, and tax
- Architect, build, and own the most complex finance data pipelines in the Finance data lake using Databricks Jobs and Lakeflow Declarative Pipelines with built-in data validation and reconciliations
- Lead the technical design of AI use cases for the Finance and Accounting organisation, including forecasting automation, anomaly detection, and natural language interfaces to financial data
- Build and maintain internal Finance applications (Databricks Apps, Genie Agents, AI/BI dashboards) that enable self-service for non-technical Finance stakeholders
- Design and deliver curated Finance datasets and enforce row-level security, data access policies, and Unity Catalog governance standards
- Define and champion coding standards, data modelling conventions, documentation practices, and testing frameworks across the Finance engineering team
- Enforce and evolve Git-based version control, pull-request review processes, and CI/CD pipelines (Declarative Automation Bundles, GitHub Actions) to satisfy SOX change management requirements
- Lead technical scoping and solutioning for requirements from Accounting, FP&A, Internal Audit, and Procurement teams
- Serve as the primary technical point of contact during financial close, ensuring data accuracy and timely resolution of pipeline issues
- Partner with IT and Engineering on new system integrations, providing detailed technical requirements and leading UAT
- Mentor junior and mid-level engineers through code reviews, pairing, and design discussions, raising the technical quality of the broader team
- Proactively identify architectural debt, performance bottlenecks, and tooling gaps, and drive resolution with minimal direction
What We Look For:
- 12+ years of experience in data engineering, analytics engineering, or finance systems, with a track record of owning complex, production-grade pipelines end-to-end
- Deep proficiency in SQL and Python; hands-on experience with Apache Spark and the Databricks platform
- Experience building and maintaining ELT/ETL pipelines from financial source systems (NetSuite, Salesforce, Stripe, Zuora, or similar) into a centralised data lake
- Strong understanding of core finance and accounting concepts, including close processes, revenue recognition, intercompany, chart of accounts, and financial reporting
- Ability to independently translate ambiguous Finance requirements into well-architected, maintainable technical solutions
- Comfortable driving technical conversations with both engineering peers and non-technical Finance stakeholders
- Experience building Finance-facing dashboards, self-service BI products, and executive reporting layers
- Familiarity with AI/ML concepts with demonstrated enthusiasm for applying them to Finance workflows
Nice to Have
- Prior experience at a high-growth SaaS or cloud infrastructure company
- Hands-on experience with 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 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
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.
About the company
Databricks
Large Enterprise
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.