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Finance Manager

Databricks

San Francisco, CAFull time5-10 yearsNot Disclosed

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aigop&lsanfp&akpisreportingaccounting + 12 more

Job Description

GAQ227R117

While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered.

Databricks is looking for an outstanding Finance Manager to join our FP&A team in our mission to help data teams solve the world's toughest problems. In this role, you will serve as the strategic finance partner to our Product Support organization, driving financial rigor and operational insights across our support offerings. You will own the Support P&L, build capacity-planning frameworks, and partner cross-functionally to shape the financial strategy behind both new and existing support investments.

As a finance professional who has experienced hyper-growth, you will solve hard problems independently, have deep experience in financial analysis and operational modeling, and have strong executive presence to communicate with senior leadership. There will be new problems to solve, from standing up KPIs for emerging support offerings to assessing the financial impact of commercialization decisions, and you will approach them with first principles thinking to come up with a solution.

Build and maintain a workforce management capacity model in partnership with Product, Support, Data Science, and StratOps teams to ensure optimal resource planning and allocation across support functions

Own and operate the Support P&L, driving visibility into cost structure, margin dynamics, and financial performance across all support offerings

Design and implement new KPIs and reporting frameworks for both new and existing Support offerings, enabling data-driven decision-making and real-time visibility into operational and financial health

Partner with Commercialization on impact analysis for new Support offerings, assessing financial viability, pricing implications, and expected return to guide go-to-market readiness

Analytically solve problems by gathering and synthesizing large datasets to deliver clear, actionable recommendations to senior leadership; lead the end-to-end recommendation process

Nurture deep, trusted partnerships with Product, Support, Data Science, StratOps, Accounting, IT, and their respective technical teams to align on strategic priorities and drive cross-functional outcomes

Guide process improvement, standardization, and reporting enhancements across Support finance workflows, installing proper controls and simplifying processes to scale with the business

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Zone 1 Pay Range

$169,100—$232,550 USD

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

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

Databricks is the Data and AI company. More than 10,000 organizations worldwide — including Block, Comcast, Condé Nast, Rivian, Shell and over 60% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to take control of their data and put it to work with 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. --- Databricks applicants Please apply through our official Careers page at databricks.com/company/careers. All official communication from Databricks will come from email addresses ending with @databricks.com or @goodtime.io (our meeting tool).

Company Size5000-10000
HeadquartersSan Francisco, CA
IndustrySoftware Development
TypePrivately Held
SpecialitiesApache Spark, Apache Spark Training, Cloud Computing, Big Data, Data Science, Delta Lake, Data Lakehouse, MLflow, Machine Learning, Data Engineering, Data Warehousing, Data Streaming, Open Source, Generative AI, Artificial Intelligence, Data Intelligence, Data Management, Data Goverance, Generative AI, and AI/ML Ops

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