Jobs at Sigma Computing

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.

Partner with the VP of Sales Engineering to run global operating rhythm, build reporting and dashboards in Sigma, optimize pre-sales funnel and POC lifecycle, lead global capacity and headcount planning, and align SE requirements across Sales, Product, RevOps, and Comp/Systems.

Manage a high-volume portfolio of mid-market SaaS customers using scalable engagement models. Drive adoption and time-to-value via self-serve onboarding, training, and automation. Monitor customer health metrics to identify churn risk and expansion opportunities, run cohort and segmentation analysis, deliver targeted communications, and collaborate with Sales, Support, and Product to enable fast issue resolution and scalable playbooks.

Lead the analytical foundation for GTM pipeline generation: define TAM/SAM, identify buying signals, measure program impact, and build cross-functional pipeline programs with Sales, BD, Marketing, and Product. Drive data-led sales plays, create supporting assets, and manage cross-functional execution to convert targeted accounts into pipeline and ARR outcomes.

Design and maintain production data pipelines and architecture across Snowflake and Databricks, scale Terraform deployments, implement data governance, build demo data processes, and collaborate cross-functionally to support analytics and product use cases.

Lead customer marketing: build a repeatable proof engine to turn customer outcomes into case studies, videos, reviews, and references; run advocacy, CAB, speaker programs, event customer voice, and distribute proof across GTM using AI-first tooling.

Lead go-to-market strategy and messaging for Sigma Apps, translating product capabilities into buyer-focused narratives. Drive feature launches, sales enablement, competitive analysis, thought leadership, and customer case studies while partnering with Product, Engineering, Design, Marketing, and Sales to shape roadmap and field communications.

Lead AI product marketing for Sigma: own positioning, go-to-market strategy, and launches for AI capabilities (LLMs, agentic workflows, coding agents). Partner with product, engineering, and sales to create messaging, enablement, thought leadership, and competitive intelligence that drives pipeline and wins enterprise AI deals.

Lead editorial strategy and run the Sigma blog end-to-end: edit technical blog content, enforce brand and editorial standards, manage AEO/SEO operations, coach contractors and internal SMEs, support executive ghostwriting, and collaborate with PMs and engineers to ensure accuracy. Drive content strategy, mentor contributors, and scale systems for consistent, high-quality content and organic growth.

Sell Sigma's analytics platform to new customers in the Bay Area. Manage the full sales cycle, generate pipeline, maintain Salesforce records, collaborate with partners, and meet quota. Engage consultatively with data and analytics stakeholders to close deals and build customer advocates.

Design, prototype, and productionize AI systems and infrastructure—recommendations, natural language interfaces, agentic workflows—partnering with product and engineering to scale ML across the full lifecycle (data curation, training, deployment, monitoring).

Design and implement backend distributed services and modern APIs to support a cloud application. Build and deploy robust, secure web applications, triage and resolve production issues, optimize SQL and database internals, and collaborate through design and code reviews using tools like Rust, Go, GraphQL, Node, and Kubernetes.

Build and maintain compiler infrastructure that translates spreadsheet interactions into optimized SQL for cloud data warehouses. Design intermediate representations and apply query optimization strategies, contribute to backend (Rust) and frontend (TypeScript) foundations, debug complex issues, and collaborate with engineers and product stakeholders to drive architecture and feature development.

Sell Sigma's data and analytics platform by owning the full sales cycle, generating pipeline, managing forecasts in Salesforce, engaging partners, closing new customers, and developing customer advocates in the BI market.

Sell Sigma's analytics platform to mid-market digital-native accounts in the Bay Area. Manage full sales cycle from prospecting to close, perform deep account planning, maintain Salesforce pipeline and forecasts, run value-based discovery, collaborate with partners, and travel (~25%) for onsite meetings to drive new revenue and customer advocacy.

Act as technical presales advisor for Sigma's analytics platform: run discovery sessions, build and present customized demos and prototypes, support RFP/RFI responses, advise on integrations and data migration, manage multiple customer engagements, and meet quarterly and annual objectives in partnership with sales and product teams.

Design, build, and operate observability platforms (metrics, logging, tracing, dashboards, alerting, APM) using Go, OpenTelemetry, and Kubernetes. Participate in on-call rotation, improve uptime, create runtime/cloud triage tools, define measurement best practices, and collaborate through design and code reviews while spending most time coding.

Manage the full commercial contract lifecycle, maintain contract database and templates, support legal operations and General Counsel, implement process improvements and KPIs, liaise with internal teams and outside counsel.

Build and optimize high-performance interactive analytics features on modern data warehouses. Design and implement full-stack features, develop performance-improving algorithms, triage and debug system issues, and collaborate across infrastructure, product, design, and customer teams to support rapid user growth.

Provide customer-facing technical support for the Sigma SaaS platform: diagnose and resolve complex SQL and data issues, collaborate with product and engineering, develop diagnostic tools and best practices, participate in on-call rotation and cross-functional improvement projects.