Sales Engineer, Data Solutions

CarGurus•Boston, MA

2d•$132,000 - $165,000•Hybrid

About The Position

CarGurus is seeking a Sales Engineer, Data Solutions to build and establish relationships with critical data customers and enable the sale of data-powered solutions. This is a quota-minded, customer-facing role focused on prospecting new buyers, conducting consultative sales conversations, translating analytical needs into the right datasets and delivery methods, closing deals, and guiding customers through data receipt. The role sits at the intersection of commercial selling and technical solutioning, requiring comfort with both business discussions and technical details like schema and delivery. This is an early-stage, build-from-scratch position where the individual will be instrumental in shaping future investments by generating customer insights.

Requirements

6+ years in B2B sales, sales engineering, data/SaaS solutions selling, or a hybrid commercial-technical role, with a track record of carrying and hitting revenue targets.
Demonstrated experience selling data, analytics, or technical products to sophisticated buyers, owning the full cycle from prospecting through close.
Comfortable with structuring and selling 5-6 figure commercial agreements.
Strong data fluency: comfort discussing schemas, granularity, aggregation, and data delivery mechanisms (cloud data sharing, SFTP, APIs) credibly with technical buyers such as data science and quant teams.
Consultative selling skills: ability to uncover a customer's underlying use case and translate it into a scoped, priced offer rather than a feature pitch.
Comfort with ambiguity and a 0-to-1 builder mindset; able to operate where pricing, packaging, and process do not yet exist and help define them.
Track record of cross-functional partnership with Product, Engineering, Strategy, Legal, and Business Operations to get deals closed and delivered.
Excellent commercial communication, executive presence, and the ability to represent a new, differentiated data offering to senior external stakeholders.

Nice To Haves

Experience selling or solutioning on Snowflake Marketplace, Snowflake data shares, data clean rooms, or external data-sharing relationships.
Background in automotive, marketplace, or B2B data/SaaS domains, and familiarity with buyers such as OEMs, lenders, insurers, investors, PE, consultants, and large dealer groups.
Experience selling API-delivered or subscription data products and structuring commercial terms (pricing ladders, usage-based or per-rooftop models).
Familiarity with competitive data providers (e.g., MarketCheck, S&P, Experian, J.D. Power, Black Book) and how enterprise data buyers evaluate and procure data.
Experience leveraging Gen AI to accelerate prospecting, research, and sales workflows.
Preferred tools: Snowflake, Salesforce (or equivalent CRM), Looker/Omni, Google/MS suite.

Responsibilities

Prospect and qualify new customers across non-dealer segments (investors, private equity, consultants, OEMs, lenders, insurers) and National Dealer accounts.
Run consultative, multi-stakeholder sales conversations to uncover customer needs and map them to CarGurus data assets.
Foster and maintain customer relationships through long, high-value enterprise sales cycles, and manage transactions through to data delivery.
Engage existing inbound interest and convert it into pipeline.
Translate customer requirements into clearly scoped offers, including asset details, structure, granularity, historical depth, refresh cadence, delivery mechanism, and commercial terms.
Advise customers on delivery approaches (e.g., Snowflake Marketplace, direct share, SFTP, API) and set expectations for current capabilities versus future builds.
Speak credibly about the substance and limitations of data assets to build customer trust.
Lead commercial conversations for Data APIs and other operational/strategic assets targeting national dealers.
Partner with National Sales, Product/Eng Data teams, and Business Operations to bring data assets to dealer partners and convert interest into trials and contracts.
Build and maintain comprehensive ideal customer profiles capturing data needs, willingness to pay, and usage frequency.
Feed structured market learnings back to Strategy, Product, Data, and Product Data Analytics teams to shape pricing, packaging, and the future data asset roadmap.