Synced from Greenhouse · Aug 20

Manager, Field Engineering

DatabricksChicago, Illinois; Connecticut; New Jersey; Remote - New York; Remote - Washington D.C.; San Francisco, CaliforniaPosted Aug 20, 2026
Engineering ManagerRemoteSenior
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Mirrored from Databricks's own Greenhouse careers system · refreshed hourly

867
Other open Databricks roles
Aug 20
Posted
Greenhouse
Applicant system
Job descriptionReq 8732052002

FEQ427R411 Req ID


Mission
Reporting to a Director, Field Engineering, the Sr. Manager, Field Engineering will help lead a team of Solutions Architects (SAs) for the Startups segment of Databricks’ Field Engineering team. You will lead and promote a diverse team focusing on enterprise software, big data/analytics, data engineering, data science, data warehousing and generative AI. Leading the technical sales team, you will partner with Sales (and other Field Engineering technical segments) to increase revenue and help customers achieve success through Databricks’ Data Intelligence Platform. You wil scale and maintain an outstanding Field Engineering team that is efficient in its operations to help accelerate Databricks' growth in the market.
 

The Impact You Will Have
You will hire, train, and grow a team of Solutions Architects for a company in high-growth mode
Make your customers extremely successful with Databricks and provide outsized value to their businesses
You will maintain a robust hiring pipeline of highly qualified, bar-raising candidates
You will establish relationships across the business to make your customers and team successful
You will keep your team of SAs ahead of the technical curve by ensuring they maintain advanced knowledge of the Databricks technology stack
You will ensure that your team is continuously learning and working to provide our customers with the most comprehensive solutions for their needs
You will engage with customers strategically at the Executive Level to drive mutually beneficial outcomes and set GTM strategy and drive world class execution towards meeting aggressive sales targets

What We Look For
Proven experience building and leading technical pre-sales teams - hiring, on-boarding, coaching and mentoring those teams to mature and grow into highly capable individual operators as well as exceptional team-players
10+ years of experience in the data space with a technical product (i.e. data warehousing, big data, machine learning, or more recently with generative AI)
Trusted advisor to technical executives that guide strategic data infrastructure decisions
Lead a team through best practices for technical qualification, technical validations, architecture discussions, and product demonstrations
Establish and foster external partnerships with systems integrators (SIs) and independent software vendors (ISVs) that maximize and accelerate client success
Strong understanding of consumption-driven business models and the recipes for long term growth and success
Experience hiring candidates that continually raise the bar, ramping them up to be successful, and promoting into larger roles
Create a positive culture and morale for the team - fostering strong working relationships between Field Engineering, Sales, and other important internal cross-functional teams
Experience working cross-functionally with other teams such as Sales, Product Management, Engineering, and Customer Success
Must be technical enough to earn the trust of Engineering talent and leadership at Databricks
Ability to influence and review complex architectures; guiding your team and customers towards ideal solutions - that scale
 

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 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.
 

Applicant Privacy Notice

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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Manager, Field Engineering
Databricks · Chicago, Illinois; Connecticut; New Jersey; Remote - New York; Remote - Washington D.C.; San Francisco, California
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