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Manage technical presales activities for enterprise customers, including discovery workshops, solution prototypes, customized demonstrations, webinars, and RFP/RFI responses. Partner with sales, product, engineering, and support teams to communicate the business value of Sigma’s cloud business intelligence platform. Advise customers on integrations, data migration, databases, cloud data warehouses, and ETL while managing multiple engagements and meeting sales objectives.

Manage technical presales activities for Sigma’s cloud business intelligence platform. Responsibilities include customer discovery, solution workshops, prototype development, customized demonstrations, presentations, RFP and RFI responses, and explaining product value. The role partners with sales, product, engineering, and support teams; advises prospects and customers on analytics, integrations, data migration, and cloud data warehouse solutions; and manages multiple enterprise engagements while meeting sales objectives.

Own EMEA revenue operations for international expansion, including market sequencing, territory design, capacity planning, operating rhythms, annual planning, pipeline management, forecasting, renewals, and upsell performance. Partner with senior sales leadership to diagnose regional risks, improve GTM efficiency, deploy AI-powered workflows, and coordinate multi-currency, partner, marketplace, legal, finance, and hiring requirements across European markets.

Technical Writing Interns will test product features and create clear, accurate documentation, tutorials, examples, release notes, diagrams, screenshots, and dynamic content. They will collaborate with engineers, designers, product managers, and writers; participate in planning and bug bashes; analyze customer feedback and metrics; publish content through a docs-as-code workflow; and complete an end-to-end documentation project during a 12-week, in-person internship.

Technical Writing Interns will test and document product features, create tutorials, examples, release notes, and visual content, and improve documentation for users and AI agents. They will collaborate with engineers, designers, product managers, and writers; participate in planning and feature testing; publish content through a docs-as-code workflow; analyze customer feedback and metrics; and own a documentation project from ideation through implementation.

Own end-to-end sales commission calculation, validation, and payout processing. Administer compensation platform and integrations (CRM, HRIS, ERP), manage quota/crediting rules, produce documentation and reports, and partner with Finance, Sales Ops, HR, and Data to improve accuracy and automate processes.

Conduct original AI/ML research in search, recommendations, NLP, and agentic workflows; prototype and productionize AI systems; address AI, analytics, and data-app UX challenges; and help build scalable infrastructure for model experimentation, training, and evaluation. The role requires a current AI/ML PhD student with strong machine learning expertise and knowledge of the full ML lifecycle.

Software Engineering Interns will design, prototype, implement, test, and deploy production features for Sigma’s cloud analytics platform. They will collaborate with engineers, product managers, designers, sales, and users; build scalable frontend and backend systems; optimize performance; document work; and use customer metrics to improve development decisions. The internship is full-time, 12 weeks, and in person in San Francisco or New York.

Build, prototype, test, and deploy production software features for Sigma’s cloud analytics platform. Interns collaborate with engineers, product managers, designers, and users; develop scalable frontend or backend systems; optimize performance; create automated unit tests; document work; and use customer metrics to improve product decisions. The role includes owning a development project from ideation through implementation while working full-time in person for 12 weeks.

Conduct original AI/ML research across search, recommendations, NLP, and agentic workflows. Prototype and productionize AI systems, address AI and analytics UX challenges, and contribute to scalable infrastructure for model experimentation, training, and evaluation. The role requires a current AI/ML PhD student with strong machine learning knowledge and an understanding of the end-to-end ML lifecycle, including data curation, training, deployment, and monitoring.