Lakebase Sales Specialist- Financial Services

Databricks Databricks · Data AI · CA · Remote · HQ Management

This role is for a Sales Specialist focused on Databricks' Lakebase, a managed Postgres offering for intelligent applications. The role involves driving revenue by identifying, qualifying, and activating Lakebase consumption within a defined territory, partnering with Account Executives. Success requires business ownership, strategic account engagement, field enablement, and market thought leadership. The ideal candidate has enterprise SaaS sales experience, understands modern data architectures, and can sell to both technical and business stakeholders.

What you'd actually do

  1. Drive new Lakebase revenue by identifying, qualifying, and driving Lakebase activations and consumption within a defined territory, in partnership with regional Account Executives and the broader account team.
  2. Lead with outcomes for key Lakebase personas — including platform teams and developers, data teams, and central IT — articulating how Lakebase helps them ship features faster, simplify operational data architectures, and improve governance and cost efficiency.
  3. Sell the value of fully-managed Postgres for intelligent applications, positioning Lakebase as the optimal choice for operational workloads that power real-time, AI-driven experiences.
  4. Run complex, multi-threaded sales cycles from discovery and value hypothesis through commercial negotiation and close, navigating executive, technical, and line-of-business stakeholders.
  5. Orchestrate proof-of-value and POCs that validate Lakebase’s benefits for OLTP-style workloads, reverse ETL, and AI/ML-driven applications, in partnership with solution architects and specialists.

Skills

Required

  • 7+ years of enterprise SaaS sales experience
  • Proven success selling data platforms, operational databases (e.g., Postgres, MySQL, cloud-native DBaaS), or adjacent data/AI infrastructure to technical buyers and business leaders.
  • Strong understanding of modern data and application architectures, including cloud-native services, microservices, event-driven systems, and how operational data underpins AI and analytics strategies.
  • Ability to sell to both technical stakeholders (developers, architects, data engineers) and business stakeholders (product leaders, operations, line-of-business owners).
  • Demonstrated experience leading specialist or overlay motions, working jointly with core Account Executives to create and progress opportunities.
  • Executive presence with the ability to whiteboard architectures, lead C-level conversations, and build trust with senior decision makers.
  • Strong value selling skills: adept at discovering pain, building a business case, and tying technical capabilities to clear, quantified outcomes.
  • Excellent communication, storytelling, and negotiation skills, with comfort presenting to both large and small audiences.
  • Bachelor’s degree or equivalent practical experience.

Nice to have

  • Experience selling Postgres, operational databases, OLTP workloads, or transactional cloud database services, ideally within large or strategic accounts.
  • Familiarity with data platforms, lakehouse architectures, and cloud ecosystems (AWS, Azure, GCP), including how operational databases fit within broader data and AI strategies.
  • Understanding of reverse ETL, real-time decisioning, and operational analytics use cases, and how they drive value for customer-facing and internal applications.
  • Exposure to AI-native and agent-driven applications that depend on low-lat

What the JD emphasized

  • consistently exceeding quota
  • selling data platforms
  • operational databases
  • AI and analytics strategies
  • technical buyers and business leaders
  • modern data and application architectures
  • cloud-native services
  • microservices
  • event-driven systems
  • operational data
  • AI and analytics strategies
  • technical stakeholders
  • business stakeholders
  • specialist or overlay motions
  • core Account Executives
  • Executive presence
  • whiteboard architectures
  • C-level conversations
  • senior decision makers
  • value selling skills
  • discovering pain
  • building a business case
  • quantified outcomes
  • communication
  • storytelling
  • negotiation skills
  • large and small audiences
  • Postgres
  • operational databases
  • OLTP workloads
  • transactional cloud database services
  • large or strategic accounts
  • data platforms
  • lakehouse architectures
  • cloud ecosystems
  • operational databases
  • data and AI strategies
  • reverse ETL
  • real-time decisioning
  • operational analytics use cases
  • customer-facing and internal applications
  • AI-native and agent-driven applications