Software Developer III (Remote)

• Design system: create the team’s design system from scratch (components, patterns, standards, and documentation), and grow and maintain it as the source of truth for the team’s UI.
• Research and personas: define the team’s user personas from the ground up; plan and run user research, and turn findings into design decisions the team can act on.
• Data-heavy UI design: produce high-fidelity prototypes and production-ready designs for analytics applications such as dashboards, data tables, charts, data visualization, and complex data-exploration workflows.
• Data visualization: make complex, technical data clear and usable, choosing the right representations for the data and the audience.
• UX and analysis: produce user flows, wireframes, and other UX deliverables; present and defend design decisions to the team and stakeholders.
• Standards and practice: establish the team’s design process, standards, and tooling, and set the bar for design quality across the applications.
• Collaboration: work closely with engineers, data scientists, analysts, and program staff to turn requirements into usable software.

Required:

• Bachelor’s degree in design, human-computer interaction, or a related field, or equivalent experience.
• 8 years of relevant software development experience
• Demonstrated experience where the primary body of work is designing data-heavy, analytics-focused products such as dashboards, data tables, charts, data visualization, and data-exploration workflows. A portfolio centered on marketing sites, content pages, or general web design does not meet this requirement.
• Demonstrated strength in data visualization: representing complex or technical data clearly.
• Proficiency in Figma.
• Demonstrated experience creating a design system from the ground up, not just working within an existing one.
• Demonstrated experience defining personas and running user research to drive design.
• Strong attention to detail and clear design reasoning, with the ability to own design decisions independently.

Desired:

• Enough data literacy to understand data structures and sources and design interfaces that fit the data, without being a data analyst or data scientist.
• Comfort learning technical or scientific domain concepts and their constraints.