Jobs at Sigma Computing

Manage strategic enterprise customer relationships, drive net dollar retention through upselling, cross-selling, and churn reduction, and develop customer success plans. Guide customers in using Sigma Computing’s analytics platform, advocate for product improvements, and deliver training, webinars, and workshops. The role requires enterprise SaaS or analytics experience, strong data and business intelligence expertise, Spanish fluency, and on-site work in New York City.

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.

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.

Manage strategic enterprise accounts, improve net dollar retention, reduce churn, identify expansion opportunities, and guide customers in adopting Sigma’s analytics platform. Develop success plans, provide analytics and business intelligence expertise, deliver training and workshops, advocate for customer needs, and collaborate with product teams. The role requires SaaS or analytics experience, complex stakeholder management, SQL, ETL, production BI implementation, and startup experience.

Manage strategic enterprise customer accounts, improve net dollar retention, reduce churn, identify expansion opportunities, and guide customers in adopting Sigma’s analytics platform. Develop success plans, deliver training and educational programs, advocate for customer needs with product teams, and use analytics expertise to drive business outcomes. The role requires 7+ years in customer success, account management, or consultative SaaS, analytics, or business intelligence roles, with experience in enterprise environments and production BI implementations.

Manage high-value SaaS customer accounts, build relationships with decision-makers, and improve net dollar retention through adoption, upselling, cross-selling, and churn reduction. Use analytics and business intelligence expertise to guide customers, develop success plans, advocate for product improvements, and deliver training, webinars, and workshops. Partner with customers to align the platform with business goals and drive measurable value.

Lead design and execution of sales productivity and ramp programs for enterprise and commercial teams. Build and maintain ramp reporting dashboards, analyze sales KPIs, collaborate cross-functionally with GTM stakeholders, manage enablement content and projects, and present insights to sales leadership to accelerate seller productivity.

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.

Design, build, and operate production data pipelines and architectures across Snowflake and Databricks. Scale demo data across cloud warehouses, partner with infrastructure for high availability, implement data governance, and collaborate cross-functionally to support analytics and GTM use cases.

Build and maintain scalable security platforms, automation, and tooling to protect data across SaaS, cloud, endpoints, collaboration tools, AI systems, and data warehouses. Develop data discovery, classification, governance, DLP, DSPM/SSPM, insider-risk, and access controls; leverage AI and automation to improve detection, prevention, and incident workflows while partnering with cross-functional teams.

Lead technical onboarding and deployment for new customers: configure environments and data connections, coach users, implement BI best practices, optimize performance, secure SSO/row-level access, enable embedded analytics and migrations, manage milestones and handoffs, and produce documentation and feedback for product and support teams.

Lead and grow a team of Support Engineers for a cloud data warehouse analytics product (Sigma). Hire, mentor, and train staff; own support metrics (CSAT, IR, SLA, TTR); improve processes; collaborate cross-functionally; analyze support data to drive product and operational improvements.

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.

Lead technical presales by discovering customer needs, building and presenting customized BI demos and prototypes, responding to RFPs/RFIs, supporting integrations and data migrations, and managing multiple customer engagements to drive adoption and sales.

Drive new customer acquisition and revenue by owning the full sales cycle from discovery to contract. Use Salesforce to manage pipeline and forecasts, engage partners, demo product, generate pipeline, and advocate for Sigma in the BI/data analytics market.

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.

Build and maintain observability platforms (metrics, logging, tracing, dashboards, alerting). Use Go, OpenTelemetry, and Kubernetes. Participate in on-call rotation, optimize cloud triage, define measurability best practices, and collaborate on design and code reviews while coding most of the time.

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).