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Synced from Greenhouse · Nov 5

Staff Forward Deployed Engineer

DatabricksUSCAPosted Nov 5, 2026
Forward Deployed EngineerStaff
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Mirrored from Databricks's own Greenhouse careers system · refreshed hourly

$220k–$302k
Compensation
921
Other open Databricks roles
Nov 5
Posted
Greenhouse
Applicant system
Job descriptionReq 8893780002

CSQ128R47

Please note: this role is hybrid and has a requirement to travel to customer locations 20-25% of the time. It requires an active Secret or Top Secret clearance OR the willingness and eligibility to obtain one. 

As a Staff Forward Deployed Engineer (FDE), you will work with federal, state, and local government customers to build and productionize solutions to their data & AI challenges using the Databricks platform. You will manage and lead technical design and implementations that integrate multiple platform capabilities for high-complexity, multi-faceted engagements. You'll also have the opportunity to influence by mentoring FDEs, customer and partner team members, as well as serve as a trusted advisor to both technical teams and senior leaders by connecting technical decisions to measureable business outcomes. In addition, you will expand platform adoption and restore confience in at-risk accounts by tailoring the approach to the customer's industry, maturity, and team context.

We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations. FDEs deliver with customer empathy, integrating with client systems, training, and other technical needs to help customers get most value out of their data. 

This is a hands-on, customer-facing role for builders who thrive at the intersection of technology and business impact. The ideal candidate combines engineering expertise with adaptability, curiosity, and a passion for working with customers and teammates to solve complex problems that drive measurable outcomes. FDEs are billable and know how to complete projects according to specification with exceptional customer empathy.

The impact you will have:

  • Production Solution Delivery: Lead cross-functional execution for complex engagements, coordinating with FDE engagement teams, Sales, Product/Engineering, xSAs and Partner teams to remove roadblocks and scale best practices. Develop frameworks and tools adopted beyond the immediate team and influences Product and Engineering by surfacing platform gaps and roadmap priorities.
  • Transformational Impact: Guide strategic customers as they implement transformational big data projects including end-to-end design, build and deployment of industry-leading big data and AI applications. Work with engagement managers to scope technical delivery work with input from the customer
  • Empower Customers: Guide customers on architecture and design; bootstrap or implement customer projects which leads to a customers' successful understanding, evaluation and adoption of Databricks.
  • Own the Architecture: Lead architecture and design decisions, ensuring solutions are secure, scalable, and aligned with both customer needs and Databricks best practices.
  • Work with the Databricks technical team, Project Manager, Architect and Customer team to ensure the technical components of the engagement are delivered to meet customer's needs.
  • Work with Engineering and Databricks Customer Support to provide product and implementation feedback and to guide rapid resolution for engagement specific product and support issues.
  • Customer Immersion: Embed with customer teams, engaging with stakeholders from technical ICs to executives to deeply understand challenges and deliver impact.
  • Reusable Assets & Scale: Contribute accelerators, frameworks, and best practices that scale impact across accounts and influence the Databricks product roadmap.

What we look for:

  • 7+ years experience in data engineering, data platforms & analytics, or software engineering
  • Expertise working with code in either Python, Scala, JavaScript/TypeScript, and modern frameworks
  • Experience with two or more common Cloud ecosystems (AWS, Azure, GCP) with expertise in at least one
  • Deep experience with distributed computing with Apache Spark™ and knowledge of Spark runtime internals
  • Experience owning large-scale projects impacting multiple teams and BUs independently and work with account teams to grow Databricks consumption
  • Deliver quantifiable impact outside of the immediate team
  • 3+ years of experience with MLOps, ML/AI models and AI APIs
  • Design and deployment of performant production end-to-end data architectures and applications that combine data pipelines, ML/AI models, and user-facing interfaces
  • Experience with technical project delivery at the Director level or above, including managing scope, timelines and measurable outcomes, translating complex concepts into actionable solutions

Preferred Qualifications: 

  • Experience working with enterprise clients at the C-level level and above and managing conflicts across a broad transformational path and stakeholder range
  • Build skills in technical areas, and demonstrate curiosity, adaptability, and eagerness to explore new technologies which support the deployment and integration of Databricks-based solutions to complete customer projects
  • Databricks Certification

 

 

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 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 anticipated 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.

 

Zone 1 Pay Range
$219,765—$302,220 USD
Zone 2 Pay Range
$219,765—$302,220 USD
Zone 3 Pay Range
$219,765—$302,220 USD
Zone 4 Pay Range
$219,765—$302,220 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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