Lead GTM Enablement & Scale Architect, Lakebase

Databricks•United States, CA

11h•$174,200 - $299,400

About The Position

Lakebase is Databricks' managed, serverless PostgreSQL database built for AI applications and agents - a category-defining product that bridges transactional, analytical, and AI workloads on a single governed platform. This is a founding enablement role. You won't be inheriting a playbook - you'll be writing it. You will own the end-to-end enablement strategy that takes Lakebase from early adoption to a product every Solutions Architect in the field can confidently qualify, position, demo, and defend in competitive situations. You will be the connective tissue between the Lakebase Product team and a global field of SAs and Partner Technical Sales - translating product capabilities into customer outcomes, and representing the field-readiness voice in Product forums where the story is unclear, where SAs stumble on positioning, where the demo surface needs to tighten before it reaches the field.

Requirements

8+ years in solutions architecture, technical pre-sales, developer relations, technical product marketing, or technical enablement, with direct experience in databases, distributed systems, or cloud data infrastructure
You've been the SA in the room: you know what it feels like to run a POC, handle objections live, and defend a technical position against a competitor. That lived experience is what makes your enablement credible
Deep hands-on knowledge of PostgreSQL, OLTP databases, or cloud database services
Builder mentality: you default to building tools, demos, and automations, not decks. You use AI tools as a daily force multiplier, not a novelty
Demonstrated ability to build enablement programs from scratch (0-to-1), not just iterate on existing content. You see a blank page as an opportunity, not a problem
Strong product instinct: you can look at a feature roadmap and immediately see how it maps to customer use cases and competitive differentiation
Experience working directly with Product and Engineering teams as a peer, not just a consumer of their content
The backbone to tell Product "the field can't sell this because X" - backed by data and field evidence
Scaling mindset: everything you build needs to work for a global field team, not a 20-person workshop. You think about leverage and automation before you think about live delivery
Exceptional communication skills - you can make complex distributed systems concepts accessible to a broad technical audience
Familiarity with the data and AI ecosystem: Lakehouse architecture, Delta Lake, vector databases, AI/ML serving patterns

Nice To Haves

Experience at a high-growth infrastructure company during a major product launch
Background in both pre-sales and post-sales technical roles - you've lived the full customer lifecycle
Hands-on experience with Databricks or competitive platforms
Experience building AI applications on operational databases (RAG patterns, agent architectures, etc.)
You've already used AI to build at scale - automating content creation, building internal tools, or shipping demos faster than anyone thought possible

Responsibilities

Own the global GTM and enablement strategy for Lakebase for Field Engineering and Partner Technical Sales - from foundational knowledge through advanced competitive positioning
Build and ship enablement at scale using AI: use vibe coding, and AI content pipelines to generate first-draft technical deep dives, competitive talk tracks, hands-on labs, and demo environments - then curate for accuracy and field impact
Drive a 'builder-first' SA culture by architecting scalable demo environments and POC repositories designed for forking, rapid customization, and deep technical proof-of-concept delivery.
Partner directly with the Lakebase Product and Engineering leadership to stay ahead of the roadmap and translate upcoming features into field-ready assets before GA
Establish a tight product feedback loop - systematically capture field friction, lost deals, and SA objections and channel them back to Product with actionable recommendations. You have the standing to tell PMs what's not working and the data to back it up
Design the competitive narrative architecture and build the "why Databricks" story that gives an SA confidence walking into a room with a customer executive.
Create scalable, multi-format enablement: Deep dives, solutions, AI role-plays, hands-on labs, and self-paced learning paths - always with a bias toward assets SAs can use in a customer conversation immediately
Build AI-powered tools that make the field smarter: agents for instant answers, AI role-plays for pitch practice, automated competitive briefs from real-time market signals
Define and track KPIs that measure field readiness, and whether SAs are actually winning more Lakebase deals
Stay a practitioner yourself: spend ~10-15% of your time in customer-facing moments - customer executive briefings, select competitive POCs, because what you build is sharper when you've defended the position in front of a customer executive, not just written it down
Take a step back, think strategically and innovate your approaches to keep up with the fast paced environment.