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Sr. Manager, Field Engineering

AI Summary
Databricks ищет Senior Manager, Field Engineering для руководства командой Solutions Architects, работающей со стартапами. Менеджер будет нанимать, развивать и удерживать сильную техническую presales-команду, а также выстраивать её операционную эффективность. Роль предполагает стратегическое взаимодействие с руководителями клиентов, Sales, Product, Engineering, Customer Success, SI и ISV-партнёрами. Ключевая цель — помогать заказчикам внедрять платформу данных и ИИ Databricks и выполнять амбициозные коммерческие цели.
Remote from
USA
Salary
Undisclosed
Department
Sales
Employment
Full Time
Experience
Director
Published
Apply before
7 Dec 2026
Listing views
26
Application actions
1
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Opportunity details

About this role.

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.

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This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightЭто руководящая роль высокого уровня, сочетающая управление людьми, глубокую техническую экспертизу в data/AI и ответственность за коммерческие результаты. Успех требует более 10 лет опыта, влияния на executive-уровне и способности масштабировать команду в быстрорастущей компании.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$225,000
US market range (per year)$180k–$280k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. Работодатель не раскрыл числовой диапазон базовой оплаты. Указана ориентировочная годовая рыночная оценка для senior-руководителя технических presales-команд в США; годовой период выведен из уровня роли и стандартной практики оплаты для full-time управленческих позиций в США.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you build and scale a Solutions Architect team for a fast-growing startup segment?

I would begin by defining the segment’s coverage model, technical competencies, success metrics, and capacity requirements. I would hire for customer empathy, technical depth, and consultative selling ability, then implement structured onboarding, mentorship, and regular skills development. I would use pipeline quality, technical win rates, time-to-productivity, and customer outcomes to continuously improve the operating model.

How do you balance technical integrity with the need to meet aggressive sales targets?

I treat technical credibility as a long-term growth driver rather than a trade-off. My team should qualify opportunities rigorously, validate architectures early, and set clear expectations about product fit and implementation requirements. This creates healthier consumption, stronger references, and more sustainable revenue.

Describe how you would engage an executive customer evaluating a modern data and AI platform.

I would connect the technical discussion to the executive’s business priorities, such as faster product delivery, governed AI adoption, cost efficiency, or improved analytics. I would bring a clear point of view on the target architecture, demonstrate measurable value, and align stakeholders on a phased adoption plan. The goal is to become a trusted advisor, not simply deliver a product demonstration.

What approach would you use to keep a Field Engineering team current on data and generative AI technologies?

I would establish a continuous learning program that combines internal enablement, hands-on labs, architecture reviews, customer-use-case sessions, and peer knowledge sharing. Individual development plans would target both platform expertise and emerging customer patterns. I would also create feedback loops with Product and Engineering so field insights improve training priorities.

How would you improve collaboration between Field Engineering and Sales?

I would define shared account-planning practices, qualification criteria, engagement rules, and joint success metrics. Regular deal reviews would focus on customer value, technical risks, mutual action plans, and resource prioritization rather than assigning blame. Consistent communication and shared accountability help both teams execute effectively.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
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