Solution Engineer

Solution Engineer at Trek Health Solution Engineer at Trek Health in Los Altos, California Posted in 1 day ago.

Type:

full-time

Job Description:

Company Description Trek Health is the financial intelligence platform for healthcare providers, built to turn price transparency data into measurable revenue outcomes. We help finance, managed care, and payer relations teams benchmark performance, identify underpayments, and approach negotiations with a defensible, data-driven strategy. Role Description Trek Health is hiring a Solutions Engineer to be the technical owner for our growing portfolio of provider clients. You'll be the trusted advisor that guides healthcare organizations through the intricate world of price transparency data and managed care contracts, helping them turn complex data into negotiating leverage with their payers. You'll partner closely with our Customer Success team to get new clients from 0 to 1 on Trek's platform, build custom analyses that drive real provider-payer conversations, and use AI tools to extend what a small team can deliver. You'll also have a weekly seat at the table with Product and Engineering, where your insights from the field directly influence what we build next. This is the third SE on a tight team, reporting to the Head of Customer Success. This is a remote role. What You'll Do Own the technical track of client onboarding

• partnering with Customer Success to get customers from kickoff to meaningful usage Be the trusted advisor on healthcare pricing and contracting
• guide customers through Trek's data, translate ambiguous questions into defensible analyses, and help them turn insights into payer negotiations Build custom reports and analyses using Trek's price transparency dataset (and other sources where helpful), making complex data accessible to non-technical stakeholders Build internal tooling using AI coding tools (Cursor, Claude, etc.

) to speed up reporting workflows and ad-hoc client work, and occasionally ship lightweight prototypes that solve specific client problems Handle complex support escalations at the intersection of data, product, and client workflow Collaborate closely with Product and Engineering to shape product roadmap and prioritization by surfacing patterns and insights from the field. What Success Looks Like Customers are quickly able to use Trek's platform to drive meaningful insights and outcomes Your analyses are used in real provider-payer conversations Product decisions improve based on insights you bring from the field The team scales its impact through tools and workflows you've built What We're Looking For Required 3+ years in a technical, client-facing role (solutions engineering, implementation, healthcare consulting, customer-facing analytics, or similar) Healthcare domain experience , specifically with claims data and/or revenue cycle data, working with providers or payers Working knowledge of payer-provider contracting (managed care contracts, rate negotiations, payer policies) Strong SQL

• comfortable writing and debugging queries against large, real-world datasets independently Strong Excel
• comfortable with pivots, advanced formulas, and turning raw data into client-ready output Hands-on experience with AI tools
• bonus if you've used AI coding tools (Cursor, Claude, etc.

) to build, automate, or solve real problems Preferred (Not Required) Direct experience designing or analyzing managed care contracts Experience building internal tools, dashboards, or BI work (Looker, Sigma, Mode, etc.) Familiarity with price transparency datasets specifically Python or other lightweight scripting comfort beyond SQL Who This Role Is Great For You enjoy combining technical depth (SQL, data, AI tooling) with client-facing problem solving, and want to turn complex data into real customer outcomes You're excited to build with AI tools and operate in a fast-paced, ambiguous environment where you can shape how the function evolves

Compensation & Benefits OTE:

$140K

• 180

K Location:

Remote Additional perks and benefits (details shared during the interview process).