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Principal Security Field Engineer

AI Summary
Databricks is seeking a principal-level security field engineer to help customers and internal field teams understand the security architecture and compliance posture of its data and AI platform. The role combines customer-facing security advisory work with scalable enablement, including white papers, slide decks, knowledge-base content, automation, and occasional code. Candidates need at least seven years of technical pre-sales or post-sales experience and the ability to explain complex security concepts clearly. Relevant expertise spans cloud and SaaS security, identity, network and endpoint security, web application security, vulnerability management, SIEM, and compliance frameworks. This is a high-autonomy role focused on multiplying impact across a large customer and employee base rather than relying solely on live meetings.
Remote from
USA
Salary
USD 216,200–371,700 / yr
Department
Cybersecurity
Employment
Full Time
Experience
Senior
Published
Apply before
9 Dec 2026
Listing views
14
Application actions
1
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Opportunity details

About this role.

RDQ327R177

While candidates in the listed location(s) are encouraged for this role, candidates in other US locations will be considered.

The Security Field Engineering team helps data teams solve the world’s toughest problems by empowering customers to understand the security of the Databricks platform and by helping account teams address questions that come up during security reviews. Reporting to the Head of Security Field Engineering, you will meet with customers to answer questions, train other Databricks team members, build customer-facing content such as slide decks, white papers, and maybe write code that customers can use. Our team prioritizes scale — we’d rather spend an hour building a doc than be in ten hours of meetings, rather deliver agent skills and knowledge base articles than be the rock star answering all the questions. If you want high growth, autonomy, and to touch all elements of security, look no further.

The impact you will have:

  • You will be viewed as a security expert as you work with field teams and customers to understand architectures, address concerns and handle compliance questions
  • Your contributions may come in multiple ways, including customer interactions, scalable slides or white paper creation, internal enablement, process improvement, automation, or technical leadership—no one excels in every area, but all are valuable
  • When you’re on the call, you will be directly appreciated. When you’re not, your impact will be felt across the company through the enablement, collateral, knowledge management, and systems you build
  • You might not come from an assurance team, but you’ll come up to speed with common security and compliance regimes to save customers hours of effort and months of uncertainty
  • You will identify customer pain points and work with product management and product marketing will improve our product and our messaging
  • You will contribute to internal-facing services and automation that make life easier for our field staff and our customers.
  • You are probably already great at AI productivity, but you’ll sit in a group focused on becoming legendary.

What we look for:

  • 7+ years of technical pre-sales or post-sales experience where you’re the person in the room explaining the hard concepts
  • Equal love of understanding complex security principles and architectures, and of communicating them simply
  • Real-world experience in multiple security domains such as IaaS+PaaS+SaaS, network and endpoint security, web applications, vulnerability management, identity management, and SIEM, though not all are needed
  • You’ve done some scripting or programming, and are excited to use AI relentlessly to scale our impact across many thousands of customers and employees.
  • Understanding of the Databricks platform is a strong plus.

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

$270,300—$371,700 USD

Zone 2 Pay Range

$243,300—$334,500 USD

Zone 3 Pay Range

$229,800—$315,900 USD

Zone 4 Pay Range

$216,200—$297,350 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.

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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

4/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a principal-level role requiring deep multi-domain security expertise, customer credibility, and the ability to translate complex technical and compliance topics into scalable guidance. Success also requires independent prioritization across customer work, internal enablement, and automation initiatives.

Salary analysis

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

Estimated job median (per year)Highly competitive
$293,950
US market range (per year)$220k–$340k
AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The employer discloses a USD base-pay range of $216,200–$371,700 across four location-based pay zones. The posting does not explicitly state an annual cadence, but yearly pay is inferred from the senior full-time US professional role and the stated base-salary amounts. Estimated US market base pay for a principal security field engineering role is $220,000–$340,000 per year; bonus and equity are excluded from these estimates.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you approach a customer security review for a complex cloud data platform?

I would first identify the customer's architecture, regulatory obligations, threat concerns, and decision timeline. I would then map the platform's controls to those requirements, clearly document shared-responsibility boundaries, involve specialists where necessary, and provide reusable evidence or reference material to reduce future review effort.

Tell us about a time you turned recurring customer security questions into a scalable solution.

I would describe the recurring questions, quantify their impact, and explain how I created a structured knowledge base, reference architecture, FAQ, or automated evidence-gathering workflow. I would measure success through reduced response time, higher field adoption, and fewer repetitive escalations.

How do you explain a complex security architecture to a non-specialist executive audience?

I begin with the business risk and desired outcome rather than technical implementation details. I use simple diagrams, plain language, and a concise explanation of controls, ownership, residual risks, and decisions needed, while keeping detailed technical material available for follow-up.

What security domains are most important when evaluating a SaaS data and AI platform?

I would assess identity and access controls, data isolation, encryption and key management, network architecture, logging and monitoring, secure software development, vulnerability management, incident response, and compliance evidence. The priority depends on the customer's data sensitivity, deployment model, and regulatory environment.

How would you use scripting or AI tools to increase the effectiveness of a security field engineering team?

I would automate repeatable tasks such as control mappings, questionnaire drafting, evidence retrieval, content classification, and knowledge-base discovery. I would validate outputs carefully, protect sensitive customer information, and design workflows that produce consistent, reviewable results for field teams.

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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