GTM Analytics Engineer

Stedi

20d•$180,000 - $230,000

About The Position

We're building a new healthcare clearinghouse In the healthcare sector, the Health Insurance Portability and Accountability Act of 1996 (HIPAA) requires that all insurance payers exchange transactions such as claims, eligibility checks, prior authorizations, and remittances using a standardized EDI format called X12 HIPAA. A small group of legacy clearinghouses process the majority of these transactions, offering consolidated connectivity to carriers and providers. Stedi is the world's only programmable healthcare clearinghouse. By offering modern API interfaces alongside traditional real-time and batch EDI processes, we enable both healthcare technology businesses and established players to exchange mission-critical transactions. Our clearinghouse product and customer-first approach have set us apart. Stedi was ranked as Ramp’s #3 fastest-growing SaaS vendor. Stedi has lightning in a bottle: engineers and designers shipping products week in and week out; a lean business team supporting the company’s infrastructure; passion for automation and eliminating toil; $92 million in funding from top investors like Stripe, Addition, USV, Bloomberg Beta, First Round Capital, and more. To learn more about how we work, watch our founder Zack’s interview with First Round Capital. What we’re looking for We’re hiring a full-stack data and analytics engineer to build and own the data foundation that will power our daily GTM operations: revenue analytics, product usage telemetry, CRM data quality, attribution, funnel performance, and forecasting. This is not a typical business analyst position. You will architect the pipelines, models, and automations that ensure our GTM teams have reliable, real-time insights into how customers discover, adopt, and expand with Stedi and our products. You will work closely with Sales, GTM Ops, Product, and Finance, executing data and analytics engineering workstreams, and conducting hands-on analysis to build the source-of-truth data for our GTM operations.

Requirements

You have exceptional analytical skills: You’ve made a career in working with data to improve products and overall business operations. You know the tools, best practices, and playbooks necessary to stand up a high-performing and organized analytics function at the company.
You know the tech stack: You write efficient SQL queries to analyze large datasets and can work with complex schemas. You're an expert with data visualization tools like Tableau, QuickSight, or Power BI. Familiarity with cloud environments (AWS, Azure, GCP).
You create and execute your own work: You notice patterns others miss and dig deep to understand root causes. You've identified data issues or operational inefficiencies that led to meaningful improvements.
You do what it takes to get the job done: You are resourceful, self-motivating, self-disciplined, and don’t wait to be told what to do. You put in the hours.
You move quickly: We move quickly as an organization. This requires an ability to match our pace and not get lost by responding with urgency (both externally to payers and internally to stakeholders), communicating what you are working on, and proactively asking for help or feedback when you need it.
You are a “bottom feeder”: You thrive on the details. No task is too small in order to find success, generate revenue, and improve our costs.

Responsibilities

Build and maintain GTM data pipelines: Own ingestion, transformation, and syncing of CRM data (HubSpot), product-usage telemetry, billing data, and third-party enrichment data in Redshift to support GTM analytics workstreams.
Develop core GTM & revenue data models: Improve operational efficiency through standardization of datasets for Sales, GTM Ops, Finance, and the executive team, while establishing common metric definitions across revenue, customer segments, and more.
Ship dashboards, alerts, and decision-making tools: Improve telemetry into business performance by building dashboards to track things like sales funnel performance and pipeline quality. Better inform GTM leadership through automation of weekly/monthly reporting and establishing a revenue forecast.
Investigate trends and build models to support sales. Accelerate sales effectiveness through implementation of alerting for critical events (e.g. pipeline drops, usage contractions, stuck deals, missed lifecycle transitions), conducting key analyses (e.g. pipeline velocity, win rates, segmentation performance), and development of GTM models (e.g. ICP scoring, account prioritization, churn risk).
Own the GTM analytics roadmap: Work with GTM leadership to maintain a backlog of GTM analytics engineering work. Proactively identify the next set of capabilities the GTM org needs (forecasting, routing logic, new usage signals, etc).

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