Teams build apps, agents, and analytics directly in Sigma, with governance and security inherited from the cloud data warehouse.
Lead the technical strategy on complex enterprise opportunities, paired with the SE assigned to the account.
Run deep technical discovery and architecture workshops with data teams, security teams, AI leads, and executive stakeholders.
Design and build custom prototypes that prove out high-value use cases, including AI-driven workflows using Sigma Assistant, Sigma agents, warehouse agents, and MCP integrations.
Present Sigma’s architecture and AI runtime story to audiences ranging from analysts to CTOs and CDOs.
Own the technical narrative on RFPs, RFIs, AI risk reviews, and security questionnaires.
Advise on integration, migration, governance, and AI patterns across Snowflake, Databricks, BigQuery, and Redshift.
Build reusable SA assets: architecture patterns, AI-workflow playbooks, competitive teardowns, and reference implementations the whole team can run.
Manage several enterprise engagements at once.
Enterprise selling. Track record of leading complex enterprise sales cycles or large BI implementations. You know how to partner with AEs and SEs to close.
Requirements
1. Use AI every day to do the job better.
If you are not using Claude, ChatGPT, Cursor, or equivalents to accelerate your account prep, architecture diagramming, prototype builds, RFP responses, and discovery synthesis, you are getting outworked by SAs who are.
We expect this hire to treat AI tooling as default infrastructure, not novelty.
2. Sell AI into the account.
You have to be fluent.
You know Sigma’s AI surface cold: Sigma Assistant in build, analyze, and plan modes, AI functions, input tables with LLM enrichment, MCP integration, and warehouse-native agent patterns.
You also speak credibly about Claude, OpenAI, Gemini, and the broader stack the customer already runs. 3. Sell against AI.
Every enterprise deal has AI competition in it.
Sometimes it is Databricks Genie.
Sigma is the AI runtime environment for the modern enterprise.
No extracts, no separate AI pipelines, no shadow stack to maintain. About the role
SAs partner with SEs on the most complex enterprise deals: architecting solutions, leading deep technical conversations, and unblocking opportunities that hinge on data infrastructure, security, or AI strategy.
Prospects and customers will come to you for architectural guidance and product expertise, especially on AI strategy, governance, and warehouse-native architecture. What you’ll do
Position Sigma against Databricks AI/BI and Genie, Snowflake Cortex Analyst, Tableau, Power BI, Looker, and AI-native entrants. Defend that position with architecture, not slogans.
Shape the product from the front line. File feature requests, write up customer patterns, and partner with Product and Engineering on what to build next, especially across the AI surface.
Deep expertise in at least one cloud data warehouse: Snowflake, Databricks, BigQuery, or Redshift.
Strong SQL and a solid grasp of modern data architecture: warehousing, modeling, governance, security.
experience with dbt, Fivetran, Matillion, or comparable tools. AI fluency.
Daily user of modern AI tools.
You can position Sigma’s AI stack against warehouse agents like Genie and Cortex Analyst, and against AI-native BI entrants, without hand-waving.
Education. Bachelor’s degree in a technical field, or equivalent experience.
Sigma is the AI Apps and agentic analytics platform built on the cloud data warehouse.
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.
Note: We have an in-office work environment in all our offices in SF, NYC, London and Sydney. Sigma’s use of AI
This hiring process utilizes artificial intelligence tools to assist in candidate screening and assessment. Our AI tools are designed to complement, not replace, human decision-making.
Experience
Technical depth. 8+ years in business intelligence, analytics engineering, or data platform roles, with at least 3 in a customer-facing technical role (SE, SA, or consulting).
Benefits
The base salary range for this position is $135k - $180k annually.
Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience.
Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work at Sigma Computing.
This role is eligible for a variable pay (based on goal achievement), stock options, as well as a comprehensive benefits package. About us:
Generous health benefits
Flexible time off policy. Take the time off you need!
Paid bonding time for all new parents
Traditional and Roth 401k
Additional details
The SA role has evolved. Here’s the version we’re hiring for.
Three things now sit at the center of how we evaluate this role.
This hire has to do all three at a senior level, with the architectural depth to back it up.
Come with a point of view on what you run, why, and how you use it to compress weeks of work into days.
Buyers want to talk about agents, MCP, A2A, context engineering, and which model is powering what.
You can architect Sigma agents and warehouse agents into a customer’s stack and explain the tradeoffs to a head of data and a CISO in the same call.
Sometimes it is a systems integrator pitching a bespoke agent built over the weekend.
You know where each of these breaks at scale, where Sigma’s warehouse-native architecture wins on governance, freshness, and cost, and how to draw the line for a skeptical CDO without hand-waving.
You can defend that position in an architecture review, on a security questionnaire, and across three follow-up calls. About Sigma
Solution Architects are the senior technical voice on our Solution Engineering team.