Design-led digital engineering for enterprise modernization and cloud optimization
QBurst is a design-driven digital engineering firm (1,001–5,000 employees, founded 2004) serving enterprise clients on modernization and cloud strategy. The tech stack spans full-stack web/mobile (React, Angular, Vue, Node.js, Python, Java, Go) paired with data and analytics tools (Tableau, Power BI, Looker Studio), cloud platforms (AWS, Azure, GCP), and container/orchestration infrastructure (Docker, Kubernetes). Current hiring is concentrated in engineering (5 senior/lead roles) with India-based recruitment, while active projects center on FinOps, ServiceNow SAM Pro, and GenAI integration—a pattern that signals operational shift toward cost governance and cloud financial management.
QBurst delivers digital transformation services to large enterprises, focusing on platform modernization, cloud migration, and cost optimization. The company operates across design, engineering, and delivery disciplines, with deep expertise in web/mobile ecosystems, enterprise cloud architecture, and analytics. Founded in 2004 and headquartered in Chantilly, Virginia, QBurst serves mid-to-large organizations navigating legacy system retirement, cloud infrastructure consolidation, and the integration of AI capabilities into existing digital solutions. The service model is project-led, with particular emphasis on reducing cloud spending and accelerating time-to-value for digital initiatives.
QBurst's stack includes React, Angular, Vue, Node.js, Python, Java, and Go for development; PostgreSQL, MySQL, MongoDB, and DynamoDB for data; AWS, Azure, and GCP for cloud; Docker and Kubernetes for orchestration; and Tableau, Power BI, and Looker Studio for analytics.
Active projects include FinOps strategy implementation, Apptio Cloudability and ServiceNow SAM Pro deployments, modernization of legacy enterprise applications, and GenAI integration into enterprise platforms.
QBurst'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.