Field CTO

Buyers want to talk about agents, MCP, A2A, context engineering, and which model powers what. You're fluent, and you can take that conversation to the most senior technical buyer in the building. You know Sigma's AI surface cold: Sigma Assistant in build, analyze, and plan modes, AI functions, input tables with LLM enrichment, MCP integration, Sigma agents, and warehouse agents. You architect these into a customer's stack, defend the tradeoffs to a head of data and a CISO in the same call, and frame the long-term AI strategy for a CTO who's deciding where to place a multi-year bet. You speak credibly about Claude, OpenAI, Gemini, and the broader stack the customer already runs.

Every enterprise deal has AI competition in it. Sometimes it's Databricks Genie. Sometimes it's Snowflake Cortex Analyst. Sometimes it's a systems integrator pitching a bespoke agent built over a weekend. You know where each one breaks at scale, where Sigma's warehouse-native architecture wins on governance, freshness, and cost, and how to draw that line for a skeptical CDO without hand-waving. You defend that position in an architecture review, on a security questionnaire, and across a six-month evaluation. Then you turn what you learn into the competitive teardowns and battlecards the entire field uses.

Sigma is the AI runtime environment for the modern enterprise. Teams build apps, agents, and analytics directly in Sigma, with governance and security inherited from the cloud data warehouse. No extracts, no separate AI pipelines, no shadow stack to maintain.

The Field CTO is the senior-most technical leader in the field organization. You partner with Solution Architects, Solution Engineers, and Enterprise Regional Sales Managers on the largest and most strategic enterprise opportunities, the ones that hinge on architecture, AI strategy, governance, or executive trust. Your job is to win the technical decision at the top of the account and to make the whole team better at winning it.

You'll work across Sales, Product, Engineering, and Support, and you'll carry real influence in all of them. Prospects and customers will come to you as a peer to their own technical leadership. Internally, you'll shape product direction, mentor the SA and SE teams, and represent Sigma's architecture and AI runtime story to the market.

Own the technical narrative across the territory's most strategic accounts, partnered with the SAs and SEs working those deals.

Lead executive-level architecture and AI strategy conversations with CTOs, CDOs, CISOs, and their senior technical teams.

Run deep technical discovery and architecture workshops, and step in to unblock the opportunities no one else can move.

Design and build production-grade prototypes and custom apps that prove out high-value use cases, including Sigma plugins, fully code-backed data apps, and AI-driven workflows using Sigma Assistant, Sigma agents, warehouse agents, and MCP integrations. You build in HTML, JavaScript, and Python, both natively in Sigma and as warehouse stored procedures.

Lead the hardest security architecture conversations: PrivateLink, OAuth, SAML, SCIM, and the governance model behind them.

Present Sigma's architecture and AI runtime story externally: analyst briefings, executive roundtables, conference stages, and CTO-to-CTO conversations.

Own the technical position on the hardest RFPs, RFIs, AI risk reviews, and security questionnaires.

Advise on integration, migration, governance, and AI patterns across Snowflake, Databricks, BigQuery, and Redshift.

Set Sigma's competitive position against Databricks AI/BI and Genie, Snowflake Cortex Analyst, Tableau, Power BI, Looker, and AI-native entrants. Defend it with architecture, not slogans, and turn it into reusable assets for the team.

Build the SA and SE playbook and the programs the field runs on: architecture patterns, AI-workflow playbooks, competitive teardowns, reference implementations, demo-build prompts, and a repeatable technical-win process.

Package domain expertise into reusable industry assets across verticals like financial services, insurance, and gaming, so a single deal's learnings compound across the territory.

Shape the product from the front line. Carry field intel directly to Product and Engineering leadership, write up customer patterns, secure early feature access, and influence the roadmap across the AI surface.

Mentor SAs and SEs. Raise the technical bar of the team and accelerate the next hire's ramp.

Run several strategic enterprise engagements at once across the territory.

Earn and maintain product, sales, and technology certifications.

Hit quarterly and annual targets set by your manager.

Technical depth. 12+ years in business intelligence, analytics engineering, or data platform roles, with at least 5 in a customer-facing technical leadership role (SA, Field CTO, principal SE, or senior consulting). Deep expertise in at least one cloud data warehouse: Snowflake, Databricks, BigQuery, or Redshift, and working fluency across the rest. Strong SQL and a deep command of modern data architecture: warehousing, modeling, governance, security.

Data engineering fluency. Hands-on experience with ETL and transformation tooling like dbt, Fivetran, Matillion, or comparable, and the judgment to architect across them.

Builder's depth. You write working code, not just diagrams. Comfortable in HTML, JavaScript, and Python, building custom apps, plugins, and AI workflows end to end, both inside the product and against the warehouse.

Security architecture. Deep command of enterprise security and identity patterns: PrivateLink, OAuth, SAML, SCIM, and the governance decisions that ride on them. You lead these conversations with a CISO, not defer them.

AI fluency at the leading edge. Daily user of modern AI tools and a credible voice on agents, MCP, A2A, context engineering, retrieval, evals, and the major model providers. You position Sigma's AI stack against warehouse agents like Genie and Cortex Analyst, and against AI-native BI entrants, without hand-waving, and you set the team's point of view.

Enterprise selling. Track record of leading and closing the most complex enterprise sales cycles or large BI implementations. You know how to partner with AEs, SAs, and SEs, and how to win the technical decision at the executive level.

Executive presence. You hold a CTO and a data engineer in the same room without switching gears awkwardly. You lead the architecture review, the boardroom briefing, and the conference keynote, and you're the person customers call when the decision is theirs to make.

Pace and energy. You operate well in a high-velocity environment. Self-starter. No hand-holding.

Team fit. You want a team that sharpens each other, and you make everyone around you better. You bring field intel back. You build the playbooks and own the next hire's ramp. Ego stays out of the room.

Education. Bachelor's degree in a technical field, or equivalent experience.

Travel. Willingness to travel up to 35%.

About us:

Sigma is the AI Apps and agentic analytics platform built on the cloud data warehouse. Business and technical teams use Sigma to explore live data, build intelligent applications, and automate critical workflows all without moving data or breaking governance. Sigma supports a spreadsheet interface, SQL, Python, and native AI in a single governed workspace, giving every team the speed to act and IT the control to scale. Sigma is trusted by more than 2,000 customers, including AMD, Duolingo, Colgate-Palmolive, and JPMorgan Chase.

Sigma announced its $80M in Series E financing in May 2026. The round was led by Princeville Capital, with new strategic investors Databricks Ventures, ServiceNow Ventures, and Workday Ventures participating alongside returning investors Altimeter Capital, Avenir Growth Capital, D1 Capital Partners, K5 Global, NewView Capital, Spark Capital, Sutter Hill Ventures, and XN. This milestone follows Sigma reaching $200M in annual recurring revenue in April 2026, with more than 100% year-over-year growth and 1.1 million new active users added in the latest fiscal year.

Come join us!