Staff Data and AI Engineer, Finance
Lead the technical design and implementation of complex finance data pipelines and AI systems at Databricks.
Skills & Technologies
Role intensity
50% coding
AI in the day-to-day
Experience building and maintaining AI use cases for Finance workflows.
Requirements
- Experience
- 12+ years
Joblaze summary
In this role, the Staff Data and AI Engineer will lead the development of complex finance data pipelines and AI solutions that support Databricks' Finance and Accounting teams. The position requires deep expertise in SQL, Python, and Apache Spark, along with a strong understanding of finance concepts and data governance. Ideal candidates will have over a decade of experience in data engineering or finance systems, and the ability to translate finance requirements into technical solutions. This role is pivotal in shaping the data infrastructure within a high-impact finance organization.
Joblaze insights
- Listed today on Joblaze — tracked directly from Databricks's career page.
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Quick facts
- Is the Staff Data and AI Engineer, Finance role remote?
- No — this is an on-site role in Bengaluru, India.
- How much experience is required?
- At least 12 years of relevant experience for this Staff Data and AI Engineer, Finance role.
- Where is the role based?
- Databricks is hiring for this position in Bengaluru, India.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Finance, Zuora, NetSuite, AI/ML, Databricks, Stripe.
- What seniority level is this role?
- Databricks targets staff-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Staff Data and AI Engineer, Finance role at Databricks.
From the original posting
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 organization. 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.
You will be embedded in a Finance organization that takes data and AI seriously, with visibility to CFO-level priorities. 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:
- Architect, build, and own the most complex finance data pipelines in the Finance DataLake, 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 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
- Design and deliver curated Finance DataLake datasets and enforce row-level security, data access policies, and Unity Catalog governance standards
- Define and champion coding standards, data modeling 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 centralized 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 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
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