Lead Technical Enablement Specialist, Field Capability & Readiness

Databricks•United States, TX

8d•$137,100 - $235,750

About The Position

Databricks is seeking a Lead Technical Enablement Specialist to define and build the capability engine for its global Field Engineering (FE) organization. The role owns a portfolio of capability and readiness initiatives, potentially spanning skills verification, technical validation, role-based readiness paths, practical challenges, credentials, and new approaches to developing and demonstrating field expertise. It will translate FE strategy, product priorities, customer needs, and changes in technical work into a focused portfolio of investments and useful experiences that help FEs grow and perform. This high-visibility, high-autonomy role combines strategy, product thinking, building, and program operations. The specialist will work across FE leadership, product and technical communities, regional teams, enablement partners, HR, and internal platform teams to define what field-ready means and embed capability development into the flow of work. The role will also help the organization adapt to AI-enabled work by evolving capability models and responsibly experimenting with AI for assessment, personalized development, expertise discovery, and program operations. The position will establish systems, governance, standards, feedback loops, and meaningful capability signals for a federated global technical organization. It will drive adoption through stakeholder engagement and field-focused experiences, help leaders understand participation, proficiency, coverage, readiness, and capability gaps, and connect demonstrated capability with development and career opportunities where appropriate. Success includes a shared point of view and roadmap, valuable readiness experiences, strong cross-functional partnerships, better visibility into capability and trends, a scalable operating model, and measurable progress in relevant business outcomes.

Requirements

At least 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 new initiatives from ambiguity, including shaping strategy, aligning stakeholders, designing and launching experiences, measuring results, and improving them over time.
Strong strategic judgment and executive presence, with the ability to partner with Directors and VPs, shape priorities, make tradeoffs, challenge assumptions constructively, and turn broad visions into clear decisions.
A product mindset, including starting with users and problems, testing assumptions, designing for adoption, and improving experiences based on evidence.
Ability to balance rigor and practicality by creating credible standards and meaningful signals without unnecessary friction for the field.
Strong data fluency, including defining useful measures, interpreting dashboards, identifying patterns, and using data and field feedback to drive decisions.
Experience partnering with internal product, engineering, or platform teams to translate program requirements into scalable tools and workflows.
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 and ability to translate between technical practitioners, SME communities, enablement teams, regional leaders, and executive stakeholders.
Strong ownership mindset, with the pace, creativity, and judgment to work effectively in a distributed, cross-functional environment.

Nice To Haves

Hands-on experience using AI to improve assessment, personalization, content, or operations.
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.

Responsibilities

Set the vision and roadmap for Field Engineering capability, translating organizational strategy, product priorities, customer needs, and changes in technical work into portfolio investments.
Own and evolve a portfolio of readiness experiences, deciding what to scale, redesign, connect, or retire across skills verification, technical demonstrations, role-based pathways, credentials, and practical application.
Invent, prototype, evaluate, and scale new ways for FEs to build and demonstrate expertise, which may include customer scenarios, technical demonstrations, peer review, contribution models, or AI-enabled assessments.
Partner with practitioners, managers, product teams, and SME communities to define credible capability standards and evidence, and embed readiness into existing FE workflows where possible.
Track how AI is changing FE workflows, technical depth, customer engagement, and delivery models; evolve capability models to assess judgment, problem-solving, architecture, collaboration, and customer impact as well as product knowledge.
Experiment responsibly with AI to improve assessment quality, personalize development, surface expertise, and scale program operations.
Partner with internal platform and engineering teams to develop simple, scalable experiences that make skills, evidence, readiness milestones, and development recommendations useful in existing systems.
Establish ownership, governance, quality standards, content and assessment lifecycles, and feedback loops across global programs, product SMEs, regional leaders, and enablement partners.
Drive adoption by developing stakeholder plans, manager engagement, narratives, and operating rhythms; listen to field feedback, remove friction, and use adoption data and feedback to improve experiences.
Define and report meaningful measures of participation, proficiency, capability coverage, readiness, and emerging gaps; use data to help leaders make investment and prioritization decisions.
Partner with FE leadership, HR, and career architecture owners to connect demonstrated capability with development conversations, specialization paths, succession planning, and career progression where appropriate.
Build a shared point of view and portfolio roadmap, launch or materially evolve relevant readiness experiences, strengthen cross-functional partnerships, improve leadership visibility, establish a scalable operating model, and demonstrate measurable progress.