Domaine
Front-end Technical Lead
Remote (Canada)
Sponsorship not specifiedDetected 25 days ago
JavaScriptReactCSSTailwind CSSCode ReviewGitGraphQLRESTProduct ManagementProduct StrategyShopifyCommunication
About the role
- Domaine is a fast growing eCommerce agency that works with some of the largest and most innovative brands and retailers in the world.
- Our team members are driven by our passion for eCommerce and our desire to do great work.
Responsibilities
- We partner closely with Shopify, allowing us to be on the cutting edge of technology and eCommerce, and providing us with a vast ecosystem of talent and opportunities.
- Domaine is looking for a Technical Lead who will be responsible for the successful delivery and implementation of all technical aspects of custom eCommerce websites built on Shopify.
- This is a client-facing role working closely with partners to understand their business needs and provide technical solutions.
- Technical Leads also work collaboratively with other departments and technology partners.
- They lead the engineering project team through implementation, including code review, frontend architecture solutioning, third-party integrations, and release management.
Requirements
- Responsible for owning the frontend feature development and driving both completion and quality Expert knowledge and experience with the Shopify eCommerce platform.
- Plans and delegates tasks to other engineering team members as required.
- SKILLS & EXPERIENCE Senior level development experience with frontend frameworks including Liquid, Javascript, React, Tailwind
- CSS, GraphQL, REST, Git Strong understanding of Shopify development including:
Skills
- Strong verbal and written communication skills to accurately describe issues to clients, developers, and product managers.
Benefits
- Our vision is to build the best Shopify agency in the world.
Company info
- Ability to work both independently and as part of a team to ensure a high level of quality.
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This listing is sourced directly from Domaine's careers page and normalized into a canonical job model.