FEQ327R222
While candidates in the listed location(s) are encouraged to apply for this role, exceptionally well-qualified candidates in other East Coast locations will also be considered.
Mission
Solutions Architects at Databricks lead the growth of the Databricks Data Intelligence Platform. As a team, we have expertise in cloud platforms, data engineering, data analytics, and data science, machine learning, and AI. As a member of our team, you will exercise and grow your expertise in those areas, using open source projects such as Apache Spark™, Delta Lake, and MLflow. This is a customer-facing role, where you will work with customers, your teammates, the product team, our post-sales team,s and partners, to identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through the implementation, to accomplish meaningful outcomes for their businesses. In this process, you will build relationships with our customers, identify and cultivate champions, and establish yourself as a trusted advisor. You will report to a Field Engineering Manager within the Financial Services team at Databricks.
The impact you will have:
- Partner with the sales team to help customers understand how Databricks can help solve their business problems
- Provide technical leadership for customers to evaluate and adopt Databricks
- Consult on big data architecture, execute proof of concepts for strategic customer projects, and validate integrations with cloud services and other 3rd party applications
- Build and present reference architectures, how-tos, and demonstrate applications for customers
- Become an expert in, and promote open source projects (Apache Spark™, Delta Lake, MLflow, and Unity Catalog) across developer communities through meetups, conferences, and webinars
- Travel to meet with customers in your territory
What we look for:
- 10+ years in a customer-facing pre-sales role, or consulting role - preferably working with big-data technologies to solve data engineering and big-data analytical challenges
- Experience designing and architecting distributed data systems
- Comfortable programming in, and debugging, at least one of: Python, SQL, Scala, Java, or R
- Experience working with global system integrators, consulting organizations, or financial services technology, or financial services data providers is a positive differentiator
- Experience building solutions with public cloud providers such as AWS, Azure, or GCP
- Experience with Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
- Experience with Data Warehousing technologies (Ex: SQL, OLTP/OLAP/DSS)
- Undergraduate degree or higher in an engineering or mathematics discipline such as Computer Science, Applied Mathematics, Electrical Engineering, etc.)
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.
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.
Databricks San Francisco, California, USA Office
160 Spear Street, San Francisco, CA, United States, 94105
Databricks Mountain View, California, USA Office
351 E Evelyn Ave Mountain View, CA USA, Mountain View, United States, 94041
Similar Jobs
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
