Posted:
9/25/2024, 10:32:37 AM
Location(s):
New York, New York, United States ⋅ New York, United States
Experience Level(s):
Senior
Field(s):
Software Engineering
Pay:
$349/hr or $725,920 total comp
P-212
While candidates in the listed location(s) are encouraged for this role, exceptionally well-qualified candidates in other East Coast locations will be considered.
Mission
Solutions Architects at Databricks lead the growth of the Databricks Unified Analytics Platform. As a team, we have expertise in cloud platforms, data engineering, data analytics, and data science, machine learning, and generative 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 teams 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 that process, you will build relationships with our customers, find and build champions, and become a trusted advisor. You will report to a Field Engineering Manager within the Financial Services team at Databricks.
The impact you will have:
What we look for:
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.
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.
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