Sales Engineer

Role overview

A boutique data and AI consultancy is hiring a hands-on Sales Engineer who owns the full client lifecycle, from initial technical discovery through the first sprint of delivery. This is a builder-seller hybrid where the person who scopes and prices the engagement is also the person writing the first lines of code before handing the work to a delivery lead. The hire carries a services revenue number against a book of accounts serving mid-market and enterprise clients across private equity, financial services, healthcare, and retail.

Responsibilities

- Own a book of new and existing accounts and carry a services revenue quota against it, with accurate forecasting - Run technical discovery independently, mapping data architectures and earning the technical win without waiting on an engineer - Scope and price engagements, including the high-risk estimate components, then defend scope through proposal and SOW stages - Stand up the first sprint of sold engagements hands-on, working directly with code before transitioning ownership to a delivery lead - Build reference architectures, demos, and proofs of concept that mirror what will actually go into production - Activate partner co-sell motions with major cloud data platform ecosystem partners - Channel field learnings back into service line definitions and pricing strategy

Requirements

- Five or more years in a client-facing technical role at a data platform, analytics, or AI company as a Solutions Architect, Sales Engineer, or technical Account Executive - Direct evidence of revenue ownership, including carried quota or named technical ownership on sizable, describable deals - Hands-on engineering within the last three years, including production SQL and Python, pipelines shipped with dbt or Airflow or similar, and after-hours production debugging - Working depth on either Snowflake or Databricks, plus enough fluency on the other to compete in a bake-off - Credibility with both executive data leaders and senior engineers in the same room - Comfort selling scope and outcomes rather than software licenses and feature lists

Nice to have

- Prior tenure inside a consultancy, systems integrator, or Big Four practice with exposure to utilization and margin mechanics - Experience selling into private equity portfolio companies or PE value creation teams - Production experience with RAG, agentic systems, or ML platforms that served real users - An existing partner network at Snowflake or Databricks that can be activated

Benefits and work setup

- Base salary plus variable compensation tied to deals sold and work that reaches production - An owned account book including the PE channel and existing accounts with room to expand - Project variety across multiple industries and technology stacks rather than a single platform for years at a stretch - Certification support across Snowflake, Databricks, AWS, GCP, and Azure - Remote-first arrangement with client travel when an engagement justifies it