.png)
P-57
At Databricks, we are inspired by helping data teams solve the world's toughest problems. 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 own missions.
We develop and operate one of the largest scale software platforms. The fleet consists of millions of virtual machines, generating terabytes of logs and processing exabytes of data per day. At our scale, we observe cloud hardware, network, and operating system faults, and our software must gracefully shield our customers from any of the above.
As a Data Scientist on the Data Team, you will help build a data-driven culture within Databricks by helping work on top priorities. The Data team also functions as an in-house, production "customer" that feeds Databricks and guides the future direction of the products.
You will report directly to the Director of Data Science.
The impact you will have:
- You will develop and implement models for cloud cost forecasting and optimization. Analyze current cloud expenditures and identify opportunities to scale cost for a growing business
- You will provide insights for future cloud usage planning and budgeting for an evolving infrastructure footprint.
- You will collaborate with Eng and Tech Ops to ensure understanding between cloud usage and goals. You will be jointly responsible for reduction in cloud costs, accuracy of forecasts, and overall impact on the business’s bottom line.
- You will gather changing requirements, define project OKRs and milestones, and communicate progress to both technical and non-technical audiences.
- You will guide junior data scientists on the team by helping with project planning, technical decisions, and code and document review.
- You will represent the data science discipline throughout the organization, having a powerful voice to make us more data-driven.
- You will represent Databricks at academic and industrial conferences and events.
What we look for:
- Understanding of cloud architecture and its possible effects on cost, performance, and scalability. Knowledge of best practices for designing scalable and cost-effective solutions in the cloud. Experience with the cost reporting and management tools of cloud service providers.
- Familiarity with specific cost optimization strategies such as reserved instances, spot instances, scalable computing resources, and efficient data storage options.
- Experience working in different teams and leading projects with a significant impact on infrastructure and operational costs.
- Experience explaining technical details and cost implications to non-technical partners.
- 7+ years of data science, machine learning, advanced analytics experience in high velocity, high-growth companies
- Experience deploying Data Science / ML solutions in production for achieving results.
- Coding skills in Python and SQL
- Experience with distributed data processing systems like Spark and familiarity with software engineering principles around testing, code reviews and deployment.
- Masters or higher in quantitative fields.
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
$192,000—$260,000 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. By providing data teams with the ability to process massive amounts of data in the Cloud and power AI with that data, Databricks helps organizations innovate faster and tackle challenges like treating chronic disease through faster drug discovery, improving energy efficiency, and protecting financial markets.
