Staff Software Engineer - Money Team
P-940
At Databricks, we are obsessed with Data + AI to solve the world's toughest problems, from security threat detection to cancer drug development. We do this by building and running the world's best data and AI infrastructure platform, so our customers can focus on the high-value challenges that are central to their missions.
Founded in 2013 by the original creators of Apache Spark™, Databricks has grown from a tiny corner office in Berkeley, CA to a global organization with over 6500 employees. Thousands of organizations, from small to Fortune 100, trust Databricks with their mission-critical workloads, making us one of the fastest-growing SaaS companies in the world.
The Money team's mission at Databricks is to maximize the value that our customers derive from their investments in data projects. We accomplish this through innovative commercialization strategies and cutting-edge engineering. Our team ensures timely, accurate, and customizable billing and usage data, alongside budgeting, forecasting, and cost optimization tools. We provide a seamless and consistent billing experience for all our customers, whether they are large enterprises or individual developers, across different pricing plans and cloud providers (AWS, GCP & Azure).
As a software engineer on the Money team, you will be closely involved in the entire billing process, including usage ingestion, metering, pricing, credits, promotions, payments, usage reporting, and cost center and budgeting. Your role is crucial in democratizing data by bringing Databricks products to market. By collaborating with marketing, product teams, commercialization experts, data scientists, IT, and customer support, you will standardize billing experiences across major cloud providers, offering our customers a unified "sky computation" experience. This role involves utilizing the latest Databricks products and tools within the ecosystem.
The impact you will have:
- Design and manage the Money systems and services, commercializing all Databricks products and offerings.
- Develop innovative primitives that enable and support various pricing strategies such as Pay-As-You-Go, commissions, credits, trials, and promotions.
- Enhance engineering and infrastructure efficiency, reliability, accuracy, and response times, including CI/CD processes, test frameworks, data quality assurance, end-to-end reconciliation, and anomaly detection.
- Collaborate with commercialization experts to develop and implement innovative pricing strategies and plans.
- Use AI and LLMs to innovate in cost insight, prediction, and optimization across various cloud providers.
- You will become an expert at using the Databricks Data + AI tools
- Provide leadership in long-term vision and requirements development for Databricks products, in partnership with our engineering teams.
- Represent Databricks at academic and industrial conferences & events.
What we look for:
- BS or higher degree in Computer Science or a related field.
- Technical leadership experience in large projects similar to those described, including near real-time large data processing and distributed service infrastructure management.
- Proven track record of building, shipping, and managing reliable, distributed services and data pipelines at scale.
- Demonstrated leadership skills and the ability to lead across functional and organizational boundaries.
- A proactive approach and a passion for delivering high-quality solutions
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.
Local Pay Range
$182,400—$247,000 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, please visit https://www.mybenefitsnow.com/databricks.
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.
Top Skills
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.
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