Sr. Solutions Architect - Public Sector (Hunter)

FEQ127R326

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 and machine learning. As a member of our team, you will exercise and develop expertise in those areas, using open-source projects such as Apache Spark, MLflow, and Delta Lake. This is a customer-facing role, where you will work with customers, your teammates, the product team, and our post-sales teams, to identify use cases for Databricks, develop architectures and solutions using our platform, and guide customers through the implementation, to accomplish value. In that process, you will build relationships with our customers, find and build champions, and become a trusted advisor. You will report to the Field Engineering Manager for the team.

• 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, implement proof of concepts for strategic customer projects, data science and machine learning projects, and validate integrations with cloud services and other 3rd party applications
• Build and present references architectures, how-tos, and demo applications for customers
• Become an expert in, and promote Databricks inspired open-source projects (Spark, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars
• Travel to customers in your region

• 8+ years in a customer-facing pre-sales, technical architecture, or consulting role
• Experience designing and architecting distributed data systems
• Comfortable programming in, and debugging, at least one of: Python, Scala, Java, SQL, or R
• Experience supporting Public Sector clients
• Have built solutions with public cloud providers such as AWS, Azure, or GCP
• Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
• Data Warehousing (Ex: SQL, OLTP/OLAP/DSS)
• [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
• US Citizen

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.

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. 

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.