Mobile app, web, and digital advertising market intelligence platform
Sensor Tower sells market intelligence on mobile apps, gaming, web traffic and digital advertising to marketers, developers and brands. Its frontend stack is unusually layered: React, Next.js, Angular, Redux, MobX and Zustand coexist over Ruby on Rails and Python, which explains why tech debt and codebase complexity top the engineering pain points. Hiring is accelerating and split between engineering and sales, with net revenue retention a stated commercial priority.
Notable leadership hires: Account Director
Sensor Tower is a privately held digital intelligence company headquartered in San Francisco, California, with 201–500 employees. Its platform measures consumer behavior and market performance across mobile apps, gaming, web, audiences, retail media and digital advertising. Customers include enterprises, brands, advertisers, marketers, and app and game developers studying competitors' usage, engagement and ad strategies. The company hires across North America, Europe, and Asia, including the United States, Japan, South Korea, India, Poland and Portugal.
Sensor Tower uses React, TypeScript, Next.js and Angular on the frontend, Ruby on Rails and Python on the backend, ClickHouse and MongoDB for data, and AWS, Docker, Kubernetes and Jenkins for infrastructure.
Sensor Tower hires in the United States, Canada, Mexico, Japan, South Korea, China, India, Thailand, Indonesia, the United Kingdom, Portugal, Poland, Estonia, Serbia, Georgia and Armenia.
Yes. Hiring is accelerating and led by engineering, followed closely by sales and product, mostly at mid and senior levels, with work focused on CI/CD, scalability and large-scale data processing.
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Sensor Tower'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.