Usage Manager Job in Databricks

Job Title: Usage Manager

Job Summary

We are seeking an experienced Usage Manager to join our team. You will support the daily Order to Cash operations by helping lead the global revenue accounting operations and revenue close process. You will play an essential role in data integrity; ensuring all customer usage information is accurately reportable. You will partner with other teams to create and promote a scalable order to cash process. This is an individual contributor position, and will be the first hire in India!

The Impact You Will Have

• Lead and manage a team of Revenue Operations Analysts, including performance management, coaching, and development.
• Manage escalations related to order-to-cash processes, ensuring timely resolution and communication with stakeholders.
• Monthly metrics highlighting performance against agreed SLAs and KPIs.
• Maintain and/or create detailed SOPs for all processes.
• Prepare proposed usage adjustments and credits, when applicable.
• Analyze usage for signed contracts with assurance to accuracy and compliance with company revenue recognition guidelines.
• Partner with Sales, Deal Desk, Billing, Engineering, IT, Legal, and Revenue Teams to develop expertise in order-to-cash policies and procedures specific to usage.
• Create and maintain detailed records in our ERP and billing platform NetSuite/Metronome to support billing, commissions, forecasting, sales, and revenue recognition processes, adhering to internal service level agreements.
• Generate and maintain comprehensive documentation of policies and processes, and assist in identifying process improvement and automation opportunities.
• Execute month-end accounting and reporting activities, ensuring timely and accurate financial close processes.
• Document controls and procedures for both new and existing business models to maintain compliance and operational excellence.
• Manage special projects as assigned, delivering accurate and timely results.
• Change management or SOPs with any system enhancements.
• Provide audit support for both control and substantive testing, ensuring compliance with internal and external requirements.
• Collaborate on process and system implementation and enhancement projects, assisting with user acceptance testing (UAT) as needed.
• Proactively identify areas for process optimization, recommending and implementing best practices for efficiency and scalability.

What We Look For

• Bachelor s degree in Finance, Accounting, Business Administration, or a related field preferred.
• Minimum of 8 years of revenue operational accounting experience, with demonstrated experience leading and managing teams.
• Strong understanding of usage-based billing models and associated financial processes.
• Proficiency with ERP systems and payment processing platforms; experience with a global ERP such as NetSuite and Salesforce is required.
• High level of analytical skills with the ability to interpret large datasets, generate reports, and perform complex reconciliations using spreadsheet software (e.g., Excel, Google Sheets).
• Ability to adapt to evolving business needs and drive change management. Must be adaptive to change.
• Proven ability to manage team performance, provide constructive feedback, and foster a positive and productive team environment.

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide including Comcast, Cond 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, please visit https://www.mybenefitsnow.com/databricks.