Job Opportunities API

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    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 Work with Accounting, FP&A, Internal Audit, and Procurement teams to gather requirements and deliver well-documented technical solutions 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 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) Working knowledge of finance and accounting concepts, including close processes, revenue recognition, and financial reporting 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 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 ben