Tiger Analytics Business Intelligence Interview Guide

Our candidates report that Tiger Analytics is looking for more than tool familiarity; they want to hear how you think through messy, business-facing problems. The SQL portion leaned hard into window functions in real scenarios — not just naming ROW_NUMBER or LAG, but explaining why one ranking or sequencing approach fits a particular use case. That pattern tells us the bar is less about syntax recall and more about whether you can translate a business question into a defensible query and defend the tradeoffs out loud.

The Tableau discussion showed the same bias toward applied judgment. Multiple candidates reported being pressed on past dashboards, architecture, performance optimization, and the reasoning behind chart, filter, and parameter choices. A recurring theme is that Tiger Analytics cares about whether you can explain why a dashboard was built a certain way, not just whether it looks polished. We also saw a notable emphasis on newer Tableau AI features, which suggests they value candidates who can connect emerging functionality to practical client work rather than treating it as a buzzword.

What makes this process distinctive is the consistency of that business-oriented lens across both technical areas. Even the final conversation stayed centered on communication, stakeholder management, and fit, which reinforces that BI here is treated as a consulting craft. The candidates who seem strongest are the ones who can move comfortably from query logic to dashboard design to client impact without sounding scripted.