O

Omni Analytics

Unified analytics platform with governed metrics

Head of Revenue Operations

Full-TimeUpdated on 10/20/2026
$240k - $300k/yr
Expert
San Francisco, CA, USA
HybridSan Francisco-based employees must work in-office three days per week; candidates elsewhere in the US work remotely.
Sales & Account ManagementSales Operations

About the job

Requirements
  • You have 5+ years in Sales Operations, Revenue Operations, or another similar role.
  • You have been an individual contributor and have at least a year of experience leading lean revenue or sales operations teams in a B2B SaaS business.
  • You can personally build and troubleshoot Salesforce workflows, data structures, automation, and integrations, and explain the decisions behind what you built.
  • You have deployed AI or model-assisted workflows that people actually use, and can describe your contribution, how you validated the outputs, and the results.
  • You can independently build and explain financial and capacity models connecting pipeline, conversion, sales cycles, representative ramp, retention, and investment. You understand unit economics and the differences between bookings, recurring revenue, recognized revenue, and cash.
  • You are comfortable investigating data with SQL, spreadsheets, and business intelligence tools. You can reconcile conflicting numbers, recognize incomplete or misleading analysis, and make recommendations with clear assumptions.
  • You have earned trust with senior leaders, constructively challenged assumptions, and resolved competing priorities. You can build a persuasive business case for headcount, tooling, or process changes.
  • You have built processes and infrastructure where little existed before, making thoughtful decisions about what to build, buy, standardize, and document.
  • You can deliver useful improvements quickly with imperfect information, explain what you prioritized and deferred, and adjust based on results and feedback.
Responsibilities
  • Lead and develop the Revenue Operations team by setting clear priorities, coaching team members, and building the case for investments in people and tools that address the company’s most important needs.
  • Turn growth targets into operating plans by partnering with Finance and go-to-market leaders on headcount and capacity modeling, segmentation, territories, and rules of engagement, connecting investment decisions to pipeline, productivity, and retention.
  • Build and improve revenue systems, staying hands-on with Salesforce and connected tools to improve data structures, integrations, routing, onboarding, and automation while establishing clear ownership and documentation.
  • Identify and deploy practical AI workflows for account research, data enrichment, pipeline inspection, and analysis; validate outputs and measure adoption and business impact.
  • Make revenue data reliable and useful by establishing consistent metric definitions, reconciling discrepancies across systems, and building reporting that helps teams understand performance and take action across the customer lifecycle.
  • Strengthen forecasting and business reviews by partnering with leaders on pipeline inspection, forecasts, quarterly business reviews, and board reporting; surface risks, explain performance, and recommend actions.
  • Build and improve sales enablement by partnering with Sales, Product, and Product Marketing on onboarding, ongoing training, and certifications; use field data to inform curriculum and measure effectiveness through time to first win, quota attainment, win rates, and average selling price.
  • Improve compensation and deal processes by partnering with Sales, Finance, and Legal on quota setting, compensation planning, quoting, approvals, and deal desk workflows, with clear handoffs for payouts and monthly close.
  • Connect sales, partnership, and post-sales operations by improving handoffs, customer health reporting, and renewal and expansion tracking so teams have the information and processes needed to manage customer relationships effectively.
Desired Qualifications
  • Experience scaling a Revenue Operations function at an early- or growth-stage SaaS company.
  • Familiarity with analytics, business intelligence, or data infrastructure products.
  • Experience with tools such as RevenueHero, LeanData, Everstage, or Common Paper, or comparable routing, compensation, and contract management systems.
  • Experience supporting partnership programs or cloud marketplace sales.

About the company

O

Omni Analytics

View
Website

Omni Analytics provides a cloud-native business intelligence and data analytics platform that unifies fast ad-hoc exploration with governed metrics. It uses a shared semantic model as the single source of truth, letting users query data via SQL, spreadsheets, or natural language while data teams maintain consistent logic, powered by the Meld engine for schema-flexible joins and write-back to central logic. The platform emphasizes governance, trust, and traceability, with AI features aligned to the semantic model to reduce untrustworthy results. Its goal is to deliver a scalable, enterprise-grade analytics layer that enables cross-department insights and embedded analytics for customers.

Company Size

501-1,000

Company Stage

Series C

Total Funding

$218.4M

Headquarters

San Francisco, California

Founded

2022

Get referred to Omni Analytics

See people who can refer or advise you

Simplify Jobs

Simplify's Take

What believers are saying

  • April 2026 Series C raised $120 million at $1.5 billion valuation.
  • Revenue grew 4x year over year, tripled year-to-date in 2026, and reached profitability in March 2026.
  • Customers like BambooHR, Cribl, and Guitar Center validate enterprise migration and embedded analytics expansion.

What critics are saying

  • Tableau, Looker, Sigma, and ThoughtSpot target Omni's core enterprise analytics budget every renewal cycle.
  • Omni depends on Snowflake, BigQuery, Databricks, and Bedrock; platform shifts can squeeze margins fast.
  • If AI-native BI commoditizes semantic layers, Omni becomes a feature, not a standalone company.

What makes Omni Analytics unique

  • Omni's governed semantic model unifies BI, spreadsheets, SQL, and AI answers across one system.
  • Founded by ex-Looker leaders, Omni sells warehouse-native analytics with embedded analytics and MCP integration.
  • Meld-style bidirectional modeling and permissions-first context make Omni harder to replace than dashboard-only tools.

Help us improve and share your feedback! Did you find this helpful?

Benefits

  • Health Insurance
  • Dental Insurance
  • Vision Insurance
  • 401(k) Retirement Plan
  • Unlimited Paid Time Off
  • Hybrid Work Options
  • Remote Work Options

Growth & Insights and Company News

Headcount

6 month growth

-2%

1 year growth

0%

2 year growth

0%
Junto Innovation Hub
Aug 14th, 2026
Artificial intelligence in construction and insurance operations.

Artificial intelligence in construction and insurance operations. The technological landscape is constantly evolving. The adoption of artificial intelligence (AI) is one of the most significant changes. These are not superficial applications. It is a deep integration that transforms traditional industries. Insurance and construction are examples. Companies such as adesso, which acquired omni:Junto, and Trunk Tools, founded by Sarah Buchner, demonstrate this trend. Artificial intelligence is becoming a central component for tackling complex challenges. It also unlocks new efficiencies. Fragmented data and the opportunity of artificial intelligence. Construction and insurance are different sectors. Both generate a huge volume of fragmented and unstructured data. An average construction site can produce 3-4 million pages of documentation. These are scattered across many systems. Sarah Buchner, founder of Trunk Tools, saw an opportunity in this disorganization. Her experience as a carpenter showed her a limitation. Traditional analysis was insufficient for complex, unstructured data. Also in the insurance sector, claims handling is complex. It requires analysis of a lot of information from different documents. omni:Junto, founded in 2015, developed artificial intelligence solutions for end-to-end automation. Its technology analyzes claims. It applies specific insurance logic. It generates traceable outputs that can be integrated into core systems. adesso acquired omni:Junto. adesso is a leading provider in Germany. It had revenue of €1.3 billion in 2024 and more than 11,100 employees. The acquisition aims to integrate AI for claims processing. Artificial intelligence is the only tool to untangle the data knot, turning it into operational knowledge. AI as an intrinsic engine of operational processes. The real revolution is not adding an AI app. It consists of integrating it deeply. Andreas Nolte of adesso made this clear. AI must connect to systems, data, and controls. These are used by insurance companies. The integration of omni:Junto into adesso's in|sure Ecosphere platform is an example. AI becomes a central component of the combined insurance portfolio. Trunk Tools integrates its AI with construction companies' systems. It creates a higher layer to analyze and automate. AI agents review contracts and technical drawings. They flag inconsistencies. They assist in managing specifications and bids. The ability to link information across the entire project is crucial. The human mind cannot compute the cascading effects of changes. An AI agent calculated that a change would have added nearly $4 million to a project. That convinced the client not to proceed. Industry knowledge in the service of innovation. The success of AI depends on understanding the industry. Sarah Buchner is an example. She has a decade of experience as a carpenter and contractor. She founded Trunk Tools in 2021. A fatal incident on a construction site pushed her to seek solutions. She earned a doctorate in data science and artificial intelligence. Her blue-collar perspective is a unique advantage. She developed products that address real needs in the field. An AI agent provided immediate instructions for a chemical exposure. This safeguarded an employee's health. In the insurance sector, the credibility of AI is crucial. It must operate under real financial, regulatory, and operational conditions. Thomas Hauschild, CEO of omni:Junto, emphasized this work. The company focused on key requirements. These include explainability and human oversight. They ensured operational reliability, data protection, and information security. Full traceability was fundamental. The credibility of AI is played out in its ability to operate under real financial, regulatory, and operational conditions. These aspects overcome the caution of regulated sectors. Construction, with thin margins, adopts new technologies slowly. Trunk Tools raised $70 million. It reached a valuation of $325 million in 2025. It learned that software alone is not enough. The company offers training and change management. This helps implement AI in large organizations. Direct experience and trust are key ingredients for adoption. AI is crossing technological boundaries. It takes root in the operational fabric of complex industries. Translating field experience into AI solutions is essential. This, combined with deep integration and attention to regulation, opens a new era. It brings efficiency and safety. For founders and innovators, there is a clear lesson. True innovation is not just technology. It lies in targeted application to solve real problems. It requires an authentic understanding of the operational context. This approach is fundamental to unlocking the full potential of artificial intelligence.

Paradime
Jun 22nd, 2026
Paradime | Omni.

Paradime | Omni. Paradime now integrates with Omni Kaustav Mitra Jun 22, 2026 I'm finally happy to announce that Omni integration is live on Paradime. Automating data engineering with AI agents requires having a shared context so that its agents can build data models and update semantics in a single workflow. Speaking with the Omni team about how Paradime Labs, Inc. can bring value to its joint customers across mid-market and enterprise accounts, it was a no-brainer. With this integration, joint customers will have the Omni context in Paradime, including lineage, data catalog, and semantic code context all in a single place. At Paradime, Paradime Labs, Inc. has built its agents that can build and run data models, self-heal broken pipelines and automate tech debt work. Its agents spin up secure, and isolated sandboxes and then traverse across multiple code repos and systems to make connected and coordinated changes. This is a big differentiator compared to closed apps like dbt Cloud(TM), where you only have dbt(TM) context compared to Paradime where the context spans the entire data platform. For example, customers can use the Paradime MCP with the BI context from a single place and ask questions about Omni, analytics, and the code behind from a single, governed MCP endpoint. Similarly, customers can use the Paradime agents to automate working on technical debt. As an example, customers are already building AI-first workflows to automate data modelling, metric creation, and semantic layer updates to take an agent-first approach to data operations. So that anyone across the business can request new data that requires new data models and the whole system can then be built in an autonomous way. This brings automation to both doing data modelling and running data pipelines. If you are exploring automating data engineering with agents, then please reach out to Paradime Labs, Inc. or sign up for a free trial - Paradime Labs, Inc.'d love to talk.

Intelligence360 News
May 21st, 2026
Omni raises $120M Series C for AI analytics platform that turns company data into trusted source of truth

Omni, an AI analytics platform, has raised $120 million in Series C funding, according to filings with the US Securities and Exchange Commission. The company provides an AI analytics platform that transforms company data into a trusted source of truth for AI applications. Built on a semantic model offering shared metrics, permissions and Git version control, Omni serves as a governed context graph for enterprises. The platform connects to company data estates and functions as a semantic foundation for native and external AI agents. Users can query data in plain English, refine results in workbooks and integrate Omni intelligence into existing tools. The company is led by chief executive officer Colin Zima.

MLQ AI
Apr 24th, 2026
Omni Analytics raises $120M Series C funding at $1.5B valuation.

Omni Analytics raises $120M Series C funding at $1.5B valuation. April 24, 2026 at 3:16 PM - by MLQ Agent Key points. * Omni Analytics raised $120 million in Series C funding led by ICONIQ, with participation from Theory Ventures, First Round Capital, Redpoint Ventures and GV123. * The round values the company at $1.5 billion, up from $650 million in March 2025, and includes a $30 million employee tender offer14. * Revenue grew 4x year-over-year, tripled year-to-date in 2026, and the company achieved profitability last month14. * Founded in 2022 by ex-Looker co-founders, Omni provides an AI analytics platform with a governed semantic data layer for enterprise customers34. * Funds will support platform development, enterprise expansion and scaling of AI features34. Omni Analytics, a San Francisco-based AI analytics platform founded by former Looker co-founders, announced a $120 million Series C funding round on April 23, 2026, at a $1.5 billion valuation. The round, led by ICONIQ with participation from existing investors, includes a $30 million employee tender offer and follows strong revenue growth. Funding details and investors. ICONIQ led the $120 million Series C round, with participation from Theory Ventures, First Round Capital, Redpoint Ventures and GV. This brings Omni's total funding to about $217 million 4. The valuation doubles the company's previous $650 million mark from March 2025 14. The employee tender offer provides liquidity to staff 12. Company background and growth. Founded in 2022 and based in San Francisco, Omni unifies business intelligence with AI through a governed semantic data layer that offers shared metrics, permissions and Git version control 134. Customers include BambooHR and Mercury. The platform serves as a trusted source of truth for AI by turning company data into a context graph for the enterprise 1. Revenue performance and use of funds. Omni reported 4x year-over-year revenue growth, with revenue tripling year-to-date in 2026, and achieved profitability for the first time last month 14. Companies are consolidating legacy BI tools, accelerating AI adoption and building AI data products with Omni 12. Proceeds will fund platform development, enterprise sales expansion, more integrations and agentic AI features 34. Valuation surge drivers. Omni's valuation jump from $650 million to $1.5 billion in just over a year underscores investor confidence in AI-driven analytics amid enterprise demand for reliable data infrastructure 14. The 4x revenue growth and recent profitability signal strong product-market fit, particularly as businesses shift from traditional BI tools to AI-integrated platforms 1. The governed semantic layer addresses key enterprise challenges like data trust and permissions, differentiating Omni in a crowded market 1. Inclusion of a $30 million tender offer reflects maturity, allowing employee liquidity while retaining talent during rapid scaling 14. Enterprise AI expansion. Omni plans to accelerate enterprise expansion and develop agentic AI features, aiming to build institutional memory that evolves over time 4. With funds targeted at integrations and sales, the company could capture more market share from legacy BI providers as AI adoption grows 34. Revenue trajectory suggests potential for further milestones, including broader profitability and possible IPO preparation 4. Competition in AI analytics will intensify, but Omni's focus on governance positions it for sustained growth in enterprise settings. Further sources. Written with AI assistance, verified and edited by its team. Questions? Contact MLQ.ai.

ConnectWeb
Apr 23rd, 2026
Omni raises Series C at $1.5B valuation, building the AI Analytics platform for the enterprise.

Omni raises Series C at $1.5B valuation, building the AI Analytics platform for the enterprise. Revenue tripled year to date after growing 4x last year, driven by enterprise AI adoption SAN FRANCISCO-BUSINESS WIRE- Omni, the AI Analytics platform, today announced its Series C funding round raising $120M at a $1.5B valuation, led by ICONIQ with participation from existing investors Theory Ventures, First Round Capital, Redpoint Ventures, and GV. The round includes a $30M employee tender offer. The round marks a significant step-up from Omni's previous $650M valuation in March 2025, driven by 4x year-over-year revenue growth from companies consolidating legacy BI use cases, accelerating AI adoption, and building AI data products with Omni. "AI isn't replacing analytics, it's expanding it," said Colin Zima, CEO & co-founder of Omni. "Dashboards and spreadsheets aren't going away, but now anyone can get instant answers without technical expertise. To capture that advantage, you need to build for it. This is how data work is changing. Our customers are already doing it - they're encoding their business context and using AI to work smarter." As companies race to connect AI to their data, many attempts fail. Most AI tools generate queries without understanding business context. They ignore permissions and return numbers that stakeholders can't verify and trust. The gap between AI spending and AI accuracy has become one of the pernicious problems in the enterprise. Omni was built for this problem. The platform is built on a semantic model, a governed context graph that stores metric definitions, business logic, and permissions for your business. The same model powers dashboards, workbooks, spreadsheets, ad-hoc SQL, and AI queries. When AI generates a query, it uses the model's definitions and access controls. The result is a governed answer, the same answer a trained data analyst would produce. What you build for great business intelligence also powers great artificial intelligence. Customers are already seeing this in production. "There's relevant, untapped business context everywhere," said Sarah Fischbach, Staff Analytics Engineer at Checkr. "Omni stands out because it makes all of our knowledge structured and durable for smarter AI. It gets more valuable as more people and more AI tools depend on it. Building in Omni's governed context graph lets us capture institutional knowledge that compounds." The approach is working at scale. BambooHR launched its Elite Analytics product to 30,000+ people in the first four months and now serves 100,000+ people with Omni. Cribl scaled company-wide self-service AI analytics after fully migrating to Omni in three months. Guitar Center consolidated multiple BI tools into Omni and built a governed, context-rich foundation for AI to serve every team. Omni's agentic capabilities extend the model's value beyond the core platform. Users can query governed data from Claude, ChatGPT, Cursor, and VS Code. Queries inherit the same business logic and permissions as native Omni queries. Users stay in the tools they already use. Data stays governed. This makes Omni the semantic foundation for both native and external AI agents. "The barrier in data has shifted from access to understanding," said Matt Jacobson, Partner at ICONIQ. "Everyone can ask questions, but without a shared layer of business context, the answers can break down. We believe the real problem was never accessibility - it was trust. And we believe Omni is building the missing layer. Data analytics is one of the top workloads for AI agents, and Omni is building a governed data layer to help those agents to get it right. We believe they will be the leading platform in the data analytics category." Omni integrates with Snowflake, Google BigQuery, Databricks, Amazon Redshift, Postgres, ClickHouse, and other major data platforms. Customers include BambooHR, Checkr, Cribl, dbt Labs, Guitar Center, Heidi AI, Mercury, Pendo, and Synthesia. About Omni Omni is the AI analytics platform. Omni turns company data into a trusted source of truth for AI. Built on a semantic model that provides shared metrics, permissions, and Git version control, Omni is the governed context graph for the enterprise. It connects to the company data estate and serves as the semantic foundation for native and external AI agents. Users ask questions in plain English, refine results in workbooks, and bring Omni intelligence into the tools teams already use. For more information, visit omni.co. Contact details: