About the Role
As a Finance Data and AI Specialist, you will be a hands-on contributor building and maintaining the data pipelines, applications, and AI-powered tools that support Databricks' Finance and Accounting organisation. You will report to the Senior Manager, Finance Data and AI and work as a core member of a team that combines engineering rigour with Finance domain knowledge.
This role is ideal for someone who is technically strong, eager to go deep on the Databricks platform, and excited to apply modern data and AI tooling to real Finance problems.
What You Will Do
- Work with Accounting, FP&A, Internal Audit, and Procurement teams to gather requirements and deliver well-documented technical solutions
- Develop and maintain ETL pipelines using Databricks Lakehouse and Python/PySpark to enhance reporting, automate journal entries, and transform core financial processes across accounting and FP&A domains, including revenue, expenses, equity, commissions, and tax
- Build and maintain finance data pipelines in the Finance data lake using Databricks Jobs and Lakeflow Spark Declarative Pipelines, including data validation and reconciliation logic
- Develop and iterate on AI-assisted tools for the Finance and Accounting organisation, including automation of manual workflows, anomaly detection, and reporting enhancements
- Contribute to the development of Finance applications (Databricks Apps, Genie Spaces, AI/BI dashboards) that enable self-service analytics for Finance stakeholders
- Build and maintain reports and dashboards for monthly, quarterly, and executive-level reporting
- Support the implementation of row-level security and data access policies across Finance DataLake datasets
- Follow Git-based version control, pull-request review processes, and CI/CD pipelines (Declarative Automation Bundles, GitHub Actions) to meet SOX change management requirements
- Support financial close by monitoring pipelines, investigating data issues, and escalating as needed
- Participate in UAT for new system integrations and assist with technical documentation
- Contribute to team coding standards and data modelling conventions under the guidance of the Finance Data Lead
What We Look For
- 7+ years of experience in finance and accounting, data engineering, analytics engineering, or finance systems
- Working knowledge of finance and accounting concepts, including close processes, revenue recognition, and financial reporting
- Proficiency in SQL and Python for pipeline development; hands-on experience with Apache Spark or the Databricks platform is a strong plus
- Experience connecting to and ingesting from financial source systems (SAP, NetSuite, Salesforce, Stripe, Zuora, or similar)
- Ability to translate Finance requirements into clean, maintainable technical solutions with guidance
- Comfortable communicating across technical and non-technical audiences
- Experience contributing to BI dashboards and self-service data products
- Curiosity about AI/ML and interest in applying new techniques to Finance workflows
Nice to Have
- Prior experience at a high-growth SaaS or cloud infrastructure company
- Exposure to AI/BI tools, Genie One, or LLM-powered applications
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.
Skills Required
- 7+ years of experience in data engineering, analytics engineering, or finance systems
- Proficiency in SQL
- Proficiency in Python
- Experience connecting to and ingesting from financial source systems (NetSuite, Salesforce, Stripe, Zuora, or similar)
- Working knowledge of finance and accounting concepts (close processes, revenue recognition, financial reporting)
- Experience contributing to BI dashboards and self-service data products
- Experience with Git-based version control, pull-request workflows, CI/CD practices, GitHub Actions, or Declarative Automation Bundles
- Experience building and maintaining finance data pipelines using Databricks Jobs and Lakeflow Spark Declarative Pipelines, including data validation and reconciliation
- Familiarity implementing row-level security and data access policies
- Ability to translate Finance requirements into clean, maintainable technical solutions and communicate across technical and non-technical audiences
- Curiosity about AI/ML and interest in applying new techniques to Finance workflows
- Hands-on experience with Apache Spark or the Databricks platform
- Prior experience at a high-growth SaaS or cloud infrastructure company
- Exposure to AI/BI tools, Genie, or LLM-powered applications
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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Healthcare Strength — Company materials highlight comprehensive medical, dental, and vision coverage alongside mental-health resources, wellness reimbursements, and business travel insurance. Offerings are described as broad and modern, with core health coverage consistently emphasized.
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Parental & Family Support — Paid parental leave is explicitly called out, with details such as up to 20 weeks for birthing parents and up to 12 weeks for non-birthing parents in the U.S. Public materials also reference family-forming support, reinforcing the focus on families.
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Wellbeing & Lifestyle Benefits — Wellness programs and perks include gym reimbursement, periodic wellness events (e.g., yoga, massages), and in-office meals and snacks in many locations. Personal development funds and discounts further enhance lifestyle and growth support.
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.
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