We are the Foundation Team, working on a Customer Data Platform—a solution that enables companies to efficiently manage end-user data. Our platform integrates data from various sources (tracking codes, chats, tickets, custom data) and transforms it into a unified customer profile.
Who We’re Looking For:
We are seeking a Mid or Senior Frontend Developer to help us build key application components: the Customer List and the Traffic Section. If you have experience in product-based companies, value proactivity, and enjoy interacting with customers, you might be the perfect fit!
Your Responsibilities:

    • Develop the Traffic Section – real-time user monitoring on the website, implementing new filters and features.
    • Build the new Customer List module from scratch – a CRM-like customer list with profiles and key data.
    • Create clear, efficient user interfaces using React + TypeScript.
    • Integrate the frontend with the backend using React Query / Redux Saga.
    • Design and implement advanced user filters for improved data management.
    • Collaborate closely with backend developers, designers, and other frontend developers.
Requirements:

    • Experience: Minimum 3 years (Mid) / 5 years (Senior) in frontend development with React.
    • Technologies: Proficiency in TypeScript, React, React Query, Redux Saga, HTML, CSS.
    • Testing: Experience with Playwright (ideally) or Cypress.
    • Build & CI/CD: Familiarity with application build tools and CI/CD processes (e.g., npm, Webpack, GitHub Actions, or similar).
    • Communication skills: Ability to engage in customer meetings and analyze their needs.
    • State management & backend communication: Experience with React Query, Redux Saga, or similar solutions.
    • UX & Performance: Strong focus on user experience (UX), including accessibility, usability, and performance optimization for smooth and intuitive interactions.
Nice-to-have:

    • Experience in building CRM or Customer Data Platform systems.
    • Knowledge of frontend performance optimization in high-volume data applications.

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