Posted:
7/25/2024, 12:12:06 PM
Location(s):
California, United States ⋅ San Francisco, California, United States
Experience Level(s):
Expert or higher ⋅ Senior
Field(s):
Finance & Banking ⋅ Sales & Account Management
Pay:
$106/hr or $220,480 total comp
GAQ324R112
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 unique role, you will be the strategic data and analytics lead for the go-to-market (GTM) finance team supporting multiple teams such as the Technical Field organization, Marketing, Customer Success, IR, & Professional Services.
As a finance professional who has experienced hyper-growth, you will work independently, have deep experience in data querying, analysis, and system improvements to achieve scale, and you can build analyses and predictive models. Gathering and curating the proper data and building an easy-to-understand narrative are skills important to success in this role. Further, we value the ability to methodically approach new challenges. You will partner directly with other members of the GTM finance leadership team and work directly with the business to improve outcomes.
The impact you will have:
What we look for:
Benefits
Comprehensive health coverage including medical, dental, and vision
401(k) Plan
Equity awards
Flexible time off
Paid parental leave
Family Planning
Gym reimbursement
Annual personal development fund
Employee Assistance Program (EAP)
Pay Range Transparency
Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents base 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 utilizes 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.
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.
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.
Website: https://databricks.com/
Headquarter Location: San Francisco, California, United States
Employee Count: 5001-10000
Year Founded: 2013
IPO Status: Private
Last Funding Type: Series I
Industries: Analytics ⋅ Artificial Intelligence (AI) ⋅ Information Technology ⋅ Machine Learning