Databricks

Builds cloud software for data analysis and AI

Senior Manager - Field Engineering, Sports

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours

Full-timeUnited StatesIn-person

About the Job

Requirements

Significant experience leading technical customer-facing teams in enterprise software, cloud, data, artificial intelligence, analytics, technical consulting, or a related environment.
Proven ability to hire high-caliber talent, develop leaders, manage performance, and make thoughtful decisions about team structure, capability mix, and resourcing.
Experience leading through other leaders or serving as a senior leader on a complex team.
Strong strategic judgment, including identifying high-impact priorities, allocating resources, managing risk, and connecting near-term execution to longer-term goals.
A track record of building repeatable operating mechanisms, playbooks, tools, or programs that scale beyond the immediate team.
Ability to influence senior internal partners across Sales, Professional Services, Solutions Architecture, Marketing, Partners, Product, Engineering, and Support.
Strong customer-advisory capability, including guiding senior stakeholders through complex technical and business decisions.
Proficient understanding of data and artificial intelligence technologies, cloud architecture, governance, security, networking, and enterprise adoption considerations.
An artificial-intelligence-first builder mindset, with evidence of applying emerging tools or approaches to improve customer outcomes and organizational effectiveness.
Demonstrated alignment with Databricks Culture Principles and ability to translate them into clear expectations and daily team practices.
Experience managing technical customer-facing teams and/or other people leaders.
Experience leading complex, multi-stakeholder customer engagements and cross-functional initiatives.
Experience in data platforms, analytics, artificial intelligence, cloud, software, technical consulting, or a related technical domain.
Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience.
Strong written, verbal, and presentation skills, as well as decision-making and stakeholder-management skills.

Responsibilities

Lead, coach, and develop Field Engineering professionals and emerging people leaders across a broader portfolio.
Set team strategy and roadmaps that connect customer needs, technical priorities, business outcomes, and broader Field Engineering goals.
Influence the portfolio’s most important priorities and help teams anticipate needs over the next 3, 6, and 12 months.
Partner with Sales and cross-functional leadership to shape technical-win strategy, resource allocation, customer coverage, and execution plans.
Build trusted relationships with senior customer stakeholders and use customer, market, and competitive insight to improve account and portfolio strategy.
Establish repeatable inspection mechanisms across teams, including portfolio reviews, customer-health reviews, technical-risk reviews, and escalation processes.
Coach leaders and senior practitioners through complex customer, technical, competitive, organizational, and performance situations.
Build and share playbooks, tools, enablement, and operating mechanisms that increase productivity and consistency beyond one team.
Influence Product, Engineering, Support, Professional Services, Marketing, and Partners on customer requirements, product gaps, and cross-functional priorities.
Use artificial intelligence and automation to create one-to-many impact across enablement, execution, forecasting, customer planning, and team productivity.
Model and strengthen a culture of psychological safety, inclusion, accountability, continuous learning, and high performance.

Desired Qualifications

Experience with Databricks or comparable data and artificial intelligence platforms.
Experience leading across multiple segments, geographies, countries, customer portfolios, or technical practices.
Experience designing or improving Field Engineering, Solutions Architecture, technical sales, customer success, or similar operating models.
Experience building partner ecosystems and cross-functional communities of practice.
Experience using artificial intelligence, automation, dashboards, or other mechanisms to improve organizational scale and repeatability.

FEQ427R388

As an Senior Manager, Field Engineering, you will lead a broader team of technical customer advisors and help shape the strategy, roadmap, and operating model for a significant Field Engineering portfolio. You will scale impact beyond your immediate team through other leaders, cross-functional initiatives, reusable practices, and strong customer and partner relationships.

This role typically leads Field Engineering professionals across a broader portfolio and may include responsibility for one or two managers. Depending on the assignment, you may support a major segment, a multi-country portfolio, or an equivalent area of complexity.

THE IMPACT YOU WILL HAVE

Lead, coach, and develop Field Engineering professionals and emerging people leaders across a broader portfolio.
Set team strategy and roadmaps that connect customer needs, technical priorities, business outcomes, and broader Field Engineering goals.
Increasingly influence the most important priorities for the portfolio and help teams see around corners over the next 3–6–12 months.
Partner with Sales and cross-functional leadership to shape technical-win strategy, resource allocation, customer coverage, and execution plans.
Build trusted relationships with senior customer stakeholders and use customer, market, and competitive insight to improve account and portfolio strategy.
Establish repeatable inspection mechanisms across teams, including portfolio reviews, customer-health reviews, technical-risk reviews, and escalation processes.
Coach leaders and senior practitioners through complex customer, technical, competitive, organizational, and performance situations.
Build and share playbooks, tools, enablement, and operating mechanisms that increase productivity and consistency beyond one team.
Influence Product, Engineering, Support, Professional Services, Marketing, and Partners on customer requirements, product gaps, and cross-functional priorities.
Use AI and automation to create one-to-many impact across enablement, execution, forecasting, customer planning, and team productivity.
Model and strengthen a culture of psychological safety, inclusion, accountability, continuous learning, and high performance.

WHAT WE LOOK FOR

Significant experience leading technical customer-facing teams in enterprise software, cloud, data, AI, analytics, technical consulting, or a related environment.
Proven ability to hire bar-raising talent, develop leaders, manage performance, and make thoughtful decisions about team structure, capability mix, and resourcing.
Experience leading through other leaders or serving as a senior leader on a complex team.
Strong strategic judgment: you can identify the highest-impact priorities, allocate resources, manage risk, and connect near-term execution to longer-term goals.
A track record of building repeatable operating mechanisms, playbooks, tools, or programs that scale beyond your immediate team.
Ability to influence senior internal partners across Sales, Professional Services, Solutions Architecture, Marketing, Partners, Product, Engineering, and Support.
Strong customer-advisory capability, including the ability to guide senior stakeholders through complex technical and business decisions.
Proficient understanding of data and AI technologies, cloud architecture, governance, security, networking, and enterprise adoption considerations.
An AI-first, builder mindset with evidence of applying emerging tools or approaches to improve customer outcomes and organizational effectiveness.
Demonstrated alignment with Databricks Culture Principles and the ability to translate them into clear expectations and daily team practices.

BASIC QUALIFICATIONS

Experience managing technical customer-facing teams and/or other people leaders.
Experience leading complex, multi-stakeholder customer engagements and cross-functional initiatives.
Experience in data platforms, analytics, AI, cloud, software, technical consulting, or a related technical domain.
Strong written, verbal, presentation, decision-making, and stakeholder-management skills.
Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent practical experience.

PREFERRED QUALIFICATIONS

Experience with Databricks or comparable data and AI platforms.
Experience leading across multiple segments, geographies, countries, customer portfolios, or technical practices.
Experience designing or improving Field Engineering, Solutions Architecture, technical sales, customer success, or similar operating models.
Experience building partner ecosystems and cross-functional communities of practice.
Experience using AI, automation, dashboards, or other mechanisms to improve organizational scale and repeatability.

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

$192,100—$264,175 USD

Zone 2 Pay Range

$192,100—$264,100 USD

Zone 3 Pay Range

$192,100—$264,100 USD

Zone 4 Pay Range

$192,100—$264,100 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.

Zone 1 Pay Range 192100 - 264175 USD
Zone 2 Pay Range 192100 - 264100 USD
Zone 3 Pay Range 192100 - 264100 USD
Zone 4 Pay Range 192100 - 264100 USD

About the Company

Databricks

Builds cloud software for data analysis and AI

Databricks builds cloud software that businesses use to organize data, analyze it, and develop AI applications. Its lakehouse architecture brings the flexible storage of a data lake together with the querying and management tools of a data warehouse. Data engineers prepare and update datasets, analysts build reports, and developers train models or create applications in a shared workspace with controls over who can use the data. The platform runs on Amazon, Microsoft, and Google clouds, and customers pay for computing usage or commit to longer contracts for discounted rates. Databricks was founded in 2013 and is headquartered in San Francisco, California.

Company size: 10,001+
Company stage: Late Stage VC
Total funding: $32.1B
Headquarters: San Francisco, CA
Founded: 2013

Recently Posted Jobs

Explore more opportunities at Databricks

See more jobs