Design & User Experience Topics
User experience design, frontend architecture, and design systems. Includes UX principles, accessibility, and design documentation.
Information Architecture and Content Design
Organizing product content and user interfaces for clarity and discoverability. Topics include information hierarchies, navigation and routing, user flows and journey mapping, wireframing and low fidelity exploration, content organization and labeling, progressive disclosure, dashboard layout and KPI placement, filters and drill downs, and ideation and sketching techniques. Evaluates the ability to align structure with user mental models and to iterate designs based on evidence.
Dashboard Architecture and Layout Design
Focuses on designing effective dashboards that surface the right information quickly and enable exploration. Topics include logical information hierarchy, placing key performance indicators prominently, grouping related metrics, choosing appropriate visualizations for the data and user tasks, and creating visual flow that guides attention. Also covers interactive features such as filtering, drill down, cross filtering, time range controls, and parameterized views; personalization and role based views; accessibility, clarity, and minimizing cognitive load; backend considerations such as data freshness, aggregation and precomputation, query performance, caching strategies, and API design for dashboards; instrumentation, testing and validation with real user scenarios, and trade offs between flexibility and simplicity.
Learning from Feedback and Iteration
Evaluate how the candidate solicits, interprets, and incorporates feedback from users, teammates, and stakeholders to improve a product, design, or process. Areas include examples of iterative cycles driven by user testing or stakeholder input, specific pivots informed by feedback, changes to documentation or deliverables based on review, techniques for gathering and prioritizing feedback, and evidence of continuous improvement and valuing diverse perspectives.
Interactive Reporting and User Experience
Design dashboards with appropriate interactivity: filters, drill-downs, tooltips, and bookmarks. Balance flexibility with simplicity; avoid analysis paralysis from too many filters. Understand how to guide users toward insights through progressive disclosure.
Company Product and Design Knowledge
Demonstrate a well researched understanding of the company, its major products, target users, market position, and core business model, combined with familiarity with the company design philosophy and visible product design patterns. Prepare to speak about flagship products and features, typical user demographics and needs, the engineering or product challenges the company faces, and how those constraints shape product and design decisions. For design roles, be ready to articulate what you admire about the company design aesthetic, specific patterns or interactions you observe, accessibility and usability trade offs, and how your own design sensibilities or past work align with and could contribute to that aesthetic. For non design roles, emphasize product priorities, technical or operational challenges, and how your skills would help advance those products. Cite concrete examples such as a recent feature, a product workflow, a known engineering challenge, or public design documentation to show you have done focused research.
Research Methodology Selection and Tradeoffs
Covers how to choose, justify, and execute research and analysis methods given research questions, stakeholder needs, and real world constraints such as limited time, budget, or access to users. Candidates should be able to compare qualitative methods such as interviews, usability testing, ethnography, and diary studies with quantitative methods such as surveys, analytics, split testing, and controlled experiments, and explain when and how to combine them into mixed methods designs. The topic includes core decision criteria and trade offs including generative versus evaluative goals, depth versus breadth, speed versus rigor, sample size and power considerations, cost versus validity, internal validity versus external generalizability, and short term versus longitudinal designs. Practical skills include aligning methodology to success metrics and business objectives, scoping minimal viable research designs, selecting sampling strategies and proxies, recruitment and instrumentation choices, pilot testing, estimation of sample size for quantitative work, mitigation of bias and threats to validity, documenting limitations and uncertainty, communicating and defending methodological choices to nonresearch stakeholders, and ensuring ethical and privacy safeguards and data quality in constrained or iterative studies.