Synced from Greenhouse · Sep 18

Solutions Engineer

DatabricksRemote - California; Remote - Colorado; Remote - Oregon; Remote - WashingtonPosted Sep 18, 2026
Solutions EngineerRemoteSenior
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Mirrored from Databricks's own Greenhouse careers system · refreshed hourly

$152k–$209k
Compensation
873
Other open Databricks roles
Sep 18
Posted
Greenhouse
Applicant system
Job descriptionReq 8756686002

The Role

As a Sr. Solutions Engineer, you will independently lead technical engagements for customers, owning discovery, solution design, and platform demonstrations. You are a builder who can code, architect, and present—combining technical depth with customer-facing skills to drive Databricks adoption. You will own frontline customer relationships and work with your Account Executive to develop technical strategies that expand platform usage within Digital Native customers.

The Impact You Will Have

  • Independently lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning
  • Build and deliver compelling proofs-of-concept and live demos on the Databricks Platform that drive technical wins
  • Own frontline technical relationships with customer engineers, data teams, and technical leads
  • Develop account-level technical strategies in partnership with your Account Executive to grow platform consumption
  • Navigate competitive landscapes by articulating Databricks differentiation through hands-on demonstrations
  • Contribute reusable technical assets (notebooks, solution accelerators, reference architectures) to the broader SA community

What We Look For

  • 4+ years in data engineering, solutions architecture, technical pre-sales, or a hands-on consulting role
  • Proficient in Python and SQL with demonstrated ability to debug, optimize, and write production-quality code — live coding is a required interview stage
  • Hands-on experience designing and implementing data solutions on at least one public cloud platform (AWS, Azure, or GCP)
  • Working knowledge of distributed data systems: Apache Spark™, Delta Lake, or equivalent (Hadoop, Kafka, Flink)
  • Experience leading technical customer conversations — discovery, whiteboarding, architecture reviews
  • Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data science/ML (model training, MLOps), or SQL analytics
  • Strong presentation and demo skills — you will build and present a live solution during the interview
  • Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)

Nice to Have:

  • Databricks certification or experience with the Databricks Platform
  • Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow
  • Background at a data/AI company, cloud provider, or technical consulting firm

Interview Process: Recruiter Screen → Hiring Manager Screen → Design and Architecture Interview → Live Coding Assessment → Build, Demo, Pitch! Presentation → Reference Check

 

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.

 

Local Pay Range
$152,300$209,450 USD

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

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.

View original posting on Greenhouse

What applying to Databricks usually looks like

Based on publicly available information, candidates applying through greenhouse for roles at Databricks can generally expect a structured process typical of this ATS. This commonly begins with an online application and resume screen, followed by a recruiter conversation to discuss background and role fit. Depending on the position, candidates may encounter technical assessments, take-home exercises, or case studies, particularly for engineering, data, and analytical roles. The process may include multiple stages such as hiring manager conversations, panel discussions, and team or cross-functional interviews. Response times vary and communication is typically managed through the greenhouse platform, including scheduling and status updates. Candidates should prepare to discuss relevant experience, technical skills, and role-specific scenarios, as greenhouse-based processes commonly emphasize structured evaluation criteria across candidates to support consistent, comparative hiring decisions throughout the pipeline.

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