Super.com operates a consumer membership platform spanning travel and fintech, with a tech stack built on React, Python, Node.js, and AWS—grounded in PostgreSQL, Kafka, and Snowflake for data. The hiring profile is heavily weighted toward interns (nearly half the active cohort) paired with selective senior/staff engineers and a scaled data team, suggesting rapid product expansion paired with infrastructure maturity demands. Active projects span fraud mitigation, identity verification, and analytics infrastructure, indicating the company is managing the operational complexity that comes with handling payments and membership scale.
Super.com is a consumer fintech and travel platform built around a membership offering (Super+). The product surfaces cashback, savings tools, travel deals, and credit-building features through a single app. The company operates from San Francisco with ~250 employees across engineering, data, marketing, product, design, operations, and finance functions. They've raised ~$150M and have processed over $2B in sales, with the membership program cited as one of the fastest-growing globally. Primary business spans two verticals—travel and fintech products—sold direct-to-consumer.
Frontend: React and JavaScript. Backend: Python, Node.js, PostgreSQL, Redis. Cloud: AWS with Docker, Kubernetes, Terraform, Helm. Data/analytics: Snowflake, Kafka, dbt, Looker, Amplitude, Cube.js. Tooling: GitLab, Jira, Datadog, Figma.
Core projects include fraud/chargeback mitigation, identity verification, AI-enabled engineering practices, analytics scaling, and web/app tracking for marketing. Also building design system evolution (Atlas) and automated dashboards.
Super.com's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.