Hire(d) better.
Hire(d) better.
Hire(d) better.
P-273
While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. #LI-REMOTE
As a Solutions Architect on the Digital Natives team, you will shape the future of the big data landscape by working with the most sophisticated data engineering and data science teams in the world.
Reporting to the Field Engineering Manager, you will collaborate with customers, product teams, and the broader customer-facing team to develop architectures and solutions using our platform and APIs. You will guide customers through the competitive landscape, best practices, and implementation; and develop technical champions along the way.
The impact you will have:
What we look for:
NOTE: If your experience isn’t a perfect match for the job description, but you feel like you’re a good fit for the role, apply. We want to work with smart, passionate, people who are good at their job, and, a lot of times, those people have non-linear career paths.
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.
Will AI replace this role?
Check AI displacement risk, transferable skills, and career alternatives for Solutions Architect - Digital Native Business
The salary range for the Solutions Architect - Digital Native Business position at Databricks is USD 140k+/yr.
The Solutions Architect - Digital Native Business position at Databricks is based in United States; San Francisco, California. This is a remote position.
The Solutions Architect - Digital Native Business position at Databricks requires 5+ yrs exp.
Key skills for the Solutions Architect - Digital Native Business position at Databricks include: machine learning, sql, python, aws, azure, google cloud, kafka, pandas, scikit-learn, pytorch.