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Salary: EUR 85,000 - 120,000 / annual
Soda is a data quality and AI performance monitoring platform used by Fortune 500 companies like Disney, Ralph Lauren, and HelloFresh. The company was founded in 2019 by veterans from Collibra and the open-source community, and is backed by top-tier investors including Point 9 Capital and Eurazeo.
You'll join as a Senior Frontend Engineer leading frontend work within one of Soda's product teams. The tech stack centers on TypeScript and Angular for the frontend, with a Java backend. You'll own the complete user experience end-to-end, from component architecture and state management through API design, with the ability to touch the backend when features require it.
Key responsibilities include: building and maintaining complex, data-dense UIs (dashboards, monitoring views, large tables, diffs, drill-downs); driving component architecture and state management; building with a component library and Storybook; writing comprehensive tests including Cypress e2e; implementing agentic features where users direct and review LLM-powered workflows; improving systems for agentic development on the frontend; shaping the APIs you consume and implementing backend changes when needed; mentoring backend-focused engineers on frontend skills; and working directly with product, design, and customers.
You'll spend most time in frontend but can ship backend endpoints without waiting for hand-offs. The team uses AI coding agents (Claude Code, Cursor) as part of daily workflow. You'll work across a distributed, async team spanning 12+ countries with senior engineers who ship.
Required: 5+ years building frontend for real products (complex SPAs with real users); expert TypeScript and deep modern framework experience (Angular preferred, but strong React/Vue engineers willing to learn Angular welcome); frontend craft (component architecture, state management, performance, responsive design); testing as a habit (e2e with Cypress/Playwright); working backend skills (read/modify Java, design APIs, write SQL); systems insight into how API shape drives UX latency; production experience with AI coding agents; independence in distributed async teams; fluent English.
Good to have: data-heavy or developer-tool product experience; design system or component library ownership; multi-tenant SaaS at scale; Python; experience building agentic workflows into products; data quality/observability industry background.
