Staff Solutions Engineer, Pre-Sales

ABOUT OMNI

Omni is the AI analytics platform that turns company data into a trusted source of truth for AI. Built on a semantic model, Omni gives teams a governed context graph, so everyone gets the same trusted answer. Ask in plain English, refine in workbooks, or bring your data into tools like Claude, ChatGPT, Cursor, and Slack.

Our team has spent decades building data platforms, and we started Omni to fix problems we saw firsthand. Today, we help customers like Condé Nast, BambooHR, and Synthesia get better answers from their data. We're headquartered in San Francisco and have raised $217M from top investors including ICONIQ, Theory Ventures, and Redpoint Ventures. Our latest $120M Series C valued us at $1.5B.

If you like helping people get more from their data, come build with us. We’d love to hear from you.

ABOUT THE ROLE

As a Staff Solutions Engineer, you'll be a trusted technical expert on the Omni platform, empowering customers to do more with their data throughout the customer lifecycle. You'll own the technical side of every deal — building one shared plan with your Account Executive and leading complex technical evaluations from discovery through proof-of-concept, hands-on in each prospect's own data and environment. You'll drive each evaluation forward, bring a clear point of view, and help shape product direction with feedback from the field, all while mentoring other SEs along the way.

RESPONSIBILITIES

- Partner with Sales leadership to provide technical expertise on our most strategic and complex opportunities, helping uncover and prove out use cases to showcase the value of the Omni platform.

- Lead technical discovery, product demonstrations, and Proofs of Concept (POCs) for our largest and most complex evaluations, enabling prospective customers on how to successfully use Omni on their data.

- Provide technical leadership across the Solutions Engineering team — mentoring SEs and shaping best practices for discovery, demos, and POCs.

- Partner with Product leadership to influence the roadmap based on patterns observed in the field.

- Represent the Solutions Engineering org in strategic, executive-level customer conversations.

- Smoothly transition trials into successful customers by partnering with post-sales teams and engaging with our partners to plan for ongoing support where needed.

ABOUT YOU

- 10+ years of pre-sales experience (Solutions Engineering, Sales Engineering, or Solutions Architecture) within business intelligence or data analytics, supporting enterprise customers.

- Deep expertise with the modern data stack, including cloud data warehouses (e.g. Snowflake, BigQuery, Databricks, Redshift), transformation tools (e.g. dbt), and the broader analytics ecosystem.

- Proven track record leading technical discovery, product demonstrations, Proofs of Concept (POCs), and technical evaluations with senior business and technical stakeholders at enterprise accounts.

- Demonstrated experience mentoring or leading other Solutions Engineers and shaping team-wide technical practices.

- Strong SQL skills, using SQL for analytics.

- Exceptional, consultative communication skills across technical, non-technical, and executive audiences.

- Prior experience with business intelligence and/or enterprise data analytics tools (such as Looker, Omni, Tableau, PowerBI, Mode, Sisense, etc).

- Experience at a high-growth, Series A-D startup.

LOCATION

This is a fully remote role open to candidates based anywhere in the US, with a preference for candidates based in the Central or Eastern time zones.

WHY JOIN US

- Passionate, supportive team with extensive experience in the space (including founders from Looker and Stitch Data) all working together to win as a team

- Health, dental, and vision insurance

- 401(k) Plan (for US-based roles)

- Flexible PTO

Omni is an equal opportunity employer. We value diversity and encourage you to apply even if you don’t check every single box. Please, let us know if you need any reasonable accommodations during the interview process.