FEQ327R25
While candidates in the listed locations are encouraged for this role, candidates in other locations will be considered.
Sr. Solution Engineers 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 Sr. Field Engineering Manager for the team.
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, 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 (Apache Spark™, Delta Lake, MLflow, and Koalas) across developer communities through meetups, conferences, and webinars
- Travel to customers in your region
What we look for:
- 5+ 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
- Expertise in at least one of the following:
- Data Engineering technologies (Ex: Spark, Hadoop, Kafka)
- Data Warehousing (Ex: SQL, OLTP/OLAP/DSS)
- Data Science and Machine Learning technologies (Ex: pandas, scikit-learn, HPO)
- [Desired] Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
- Secret security clearance or willingness to obtain one is nice to have
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.
Skills Required
- 5+ 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
- Expertise in at least one: Data Engineering technologies (Spark, Hadoop, Kafka); Data Warehousing (SQL, OLTP/OLAP/DSS); Data Science/ML technologies (pandas, scikit-learn, HPO)
- Degree in a quantitative discipline (Computer Science, Applied Mathematics, Operations Research)
- Secret security clearance or willingness to obtain one
Databricks Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Databricks and has not been reviewed or approved by Databricks.
-
Equity Value & Accessibility — Equity grants and RSUs are a major part of total compensation and are highlighted for meaningful upside potential. Stock-based awards and refreshers contribute to strong overall pay positioning across senior technical and go-to-market roles.
-
Healthcare Strength — Medical, dental, and vision coverage are complemented by mental-health resources, an EAP, and wellness reimbursements. Health benefits are consistently framed as comprehensive and competitive.
-
Parental & Family Support — Paid parental leave for all parents, fertility support, and backup care options provide tangible assistance for family needs. Hybrid work norms and team-day structure further ease coordination for caregivers.
Databricks Insights
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.
.png)
