Omni - Frontend Engineer, Data Visualization
Requirements
• Familiarity with data warehouses like Snowflake, BigQuery, or Redshift • Background in data viz research or academic work • Our Stack • Our Stack • JavaScript / TypeScript • React with Remix • Vega / Vega Lite / Echarts • Location • Location • This role is based in San Francisco, or remote for candidates based near one of Omni's engineering hubs (Philadelphia, Boulder/Denver, Santa Cruz, or Seattle); final-round interviews are conducted in person.
Responsibilities
• Set technical direction and North Star for Omni's data visualization capabilities • Partner with the Product Manager and engineering team to translate viz strategy into shipped features • Bring industry best practices and experience to raise the bar on visualization quality and performance • Design and build front-end visualization components and the underlying data pipelines that power them • Mentor and technically guide engineers already working on the visualization work stream • Move quickly and ship iteratively, refining based on customer feedback • Use AI coding tools (e.g., Claude Code) to maximize velocity and focus on the highest-leverage technical work • 5+ years of software engineering experience, including 2+ years operating at a senior level • Deep, demonstrable experience in data visualization, ideally with industry recognition or a strong portfolio of shipped visualization work • Strong proficiency in TypeScript or JavaScript • Experience with data or business intelligence tools or applications (e.g., SQL, Looker, Tableau, Mode, Amplitude, Google Analytics) • Demonstrated ability to set technical vision and influence a team without requiring formal authority • Proficiency with AI coding tools and workflows (e.g., Claude Code, Cursor)
Benefits
• Base Salary $160K – $250K • Offers Equity • Upload your resume here to autofill key application fields. • Drop your resume here! • Parsing your resume. Autofilling key fields... • or drag and drop here • JavaScript / TypeScript • None of the above • 1 – Occasional: I sometimes use AI chat or autocomplete for snippets, syntax questions, or debugging (e.g., asking ChatGPT why a CSS layout is breaking). • 2 – Regular assistant: AI is part of my daily workflow. I use it to generate components, write tests, refactor code, or explain unfamiliar parts of a codebase, and I review everything it produces. • 3 – Agent-driven: I hand off full tasks to AI coding agents (e.g., Claude Code, Cursor agent mode), such as building a feature across multiple files, turning a design into working UI, or running and fixing tests, then review and ship the result. • 4 – Orchestrator/builder: I run multiple agents in parallel, build custom tooling or workflows for them (e.g., rules files, MCP integrations, design-to-code pipelines), or build AI-powered features into the product itself. • None of the above • Greencard Holder
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