Responsibilities

The Field Engineering role is changing quickly. AI is changing how technical work gets done, products and customer needs are evolving faster, and the capabilities that distinguish an exceptional FE today will not be exactly the same ones that matter tomorrow.
Databricks is looking for a Lead Technical Enablement Specialist to help define and build the capability engine for our global Field Engineering organization. You will shape how FEs build expertise, demonstrate readiness, share what they know, and apply their capabilities with customers.
This role owns a portfolio, not a single program. That portfolio may include skills verification, technical validation, role-based readiness paths, practical challenges, and new approaches we have not yet imagined. Your job is to understand where the field is headed, identify the capabilities that will matter most, and turn that insight into experiences and systems that help FEs grow and perform.
This is a high-visibility, high-autonomy role for someone who wants to build. You will work with FE leaders, product and technical communities, regional teams, enablement partners, HR, and internal platform teams to define what “field-ready” means and make it useful in the flow of work. You will have the opportunity to influence how a global technical organization develops - and to create programs that become part of how Databricks operates.
The best person for this role is equal parts strategist, product thinker, builder, and operator. You can see around corners, create structure from ambiguity, earn trust with senior stakeholders, and turn an idea into something the field actually uses. You are energized by the possibility of using AI not only as a topic to teach, but as a catalyst to redesign how capability is built, measured, and scaled.
Set the vision and roadmap for FE capability. Develop a clear point of view on how Databricks should build, demonstrate, recognize, and continuously evolve field expertise. Translate FE strategy, product priorities, customer needs, and the changing nature of technical work into a focused portfolio of investments.
Own and evolve a portfolio of readiness experiences. Bring together existing programs and new opportunities across skills verification, technical demonstrations, role-based pathways, credentials, and practical application. Decide what to scale, redesign, connect, or retire to keep the portfolio coherent and valuable.
Invent new ways for FEs to build and prove expertise. When the field needs a new capability, design the right experience - not automatically another course. This could be a customer scenario, a live technical demonstration, a peer review, a contribution model, an AI-enabled assessment, or something entirely new. Prototype quickly, learn from the field, and scale the strongest ideas.
Make readiness relevant to the work FEs actually do. Partner with practitioners, managers, product teams, and SME communities to define credible standards and evidence of capability. Embed development and validation into existing FE workflows wherever possible, making readiness a pull-based experience rather than an additional layer of process.
Help the organization adapt to an AI-enabled future. Stay close to how AI is changing FE workflows, technical depth, customer engagement, and delivery models. Ensure our capability models measure judgment, problem-solving, architecture, collaboration, and customer impact - not just static product knowledge. Experiment with AI to improve assessment quality, personalize development, surface expertise, and scale program operations responsibly.
Create the systems and signals that make capability visible. Partner with internal platform and engineering teams to turn program concepts into simple, scalable experiences. Ensure that skills, evidence, readiness milestones, and development recommendations are useful to FEs, managers, and leaders in the systems they already use.
Build the operating model for a federated technical organization. Establish clear ownership, governance, quality standards, content and assessment lifecycles, and feedback loops across global programs, product SMEs, regional leaders, and enablement partners. Create mechanisms that let expertise scale without centralizing every decision.

Qualification

A product mindsetStrong data fluencyExcellent communication skillsA strong ownership mindsetExperience designing skills taxonomiesFamiliarity with learning scienceWhy This Role Matters

Required

6+ years of experience in technical enablement, product management, learning and development, consulting, field engineering, or program leadership within a high-growth technology company.
A track record of building and scaling something new from ambiguity. You have shaped the strategy, aligned stakeholders, designed the experience, launched it, measured it, and improved it over time.
Strong strategic judgment and executive presence. You can partner with Directors and VPs to shape priorities, make tradeoffs, challenge assumptions constructively, and turn a broad vision into clear decisions.
A product mindset. You start with the user and the problem, test assumptions, design for adoption, and continuously improve the experience based on evidence.
The ability to balance rigor with practicality. You know how to create credible standards and meaningful signals without adding unnecessary friction for the field.
Strong data fluency. You can define useful measures, interpret dashboards, identify patterns, and use data and field feedback to drive decisions.
Experience partnering with internal product, engineering, or platform teams to turn program requirements into scalable tools and workflows.
Genuine curiosity about AI and its impact on technical work, customer engagement, and organizational capability. Hands-on experience using AI to improve assessment, personalization, content, or operations is a plus.
Enough technical fluency in data and AI to work credibly with technical experts and evaluate whether readiness standards are relevant and meaningful - or the curiosity and learning agility to build that fluency quickly.
Excellent communication skills. You can translate between technical practitioners, SME communities, enablement teams, regional leaders, and executive stakeholders.
A strong ownership mindset, with the pace, creativity, and judgment to operate effectively in a distributed, cross-functional environment.

Preferred

Experience designing skills taxonomies, competency frameworks, technical certifications, assessment models, or role-based capability systems.
Experience building community-driven models for sharing and validating expertise, such as peer review, SME networks, contribution-based credentials, or practitioner communities.
Familiarity with learning science, adult learning, assessment design, or evidence-based evaluation.
Experience integrating capability or enablement programs with internal platforms, such as skills systems, LMS platforms, CRM systems, or custom enterprise tools.
Experience with industry-specific enablement or vertical go-to-market strategies in enterprise software.
Experience in a customer-facing technical role, such as solutions architecture, sales engineering, consulting, technical account management, or data and AI engineering.
Why This Role Matters
A global FE organization cannot scale its impact through content and training alone. It needs a shared view of what great looks like, practical ways for people to build and demonstrate expertise, strong communities that spread knowledge, and useful signals that help leaders invest in the right capabilities.

Sr. Counsel, Competition at Databricks · LumiJobs

Sr. Counsel, Competition

Responsibilities

Qualification

Required

Preferred

Benefits

Company

Databricks

More roles at Databricks