Infosys Data Analyst Interview Guide

This guide is framed as a Data and Business Analytics interview because the available evidence sits in the broader analytics family rather than a cleanly separate Data Analyst lane.

Our candidates report that Infosys is far less interested in flashy problem-solving than in whether you can explain the fundamentals cleanly and tie them back to real work. Across experiences, the strongest signal was resume ownership: interviewers repeatedly dug into listed projects, daily responsibilities, and exact contributions, and candidates who could walk through those details confidently tended to do well. Even when the tone was calm and conversational, the bar was still there — not for advanced algorithms, but for crisp explanations of SQL, DBMS, OOPs, and core analytics concepts.

A recurring theme is that the company seems to value practical fluency over depth for depth’s sake. We saw basic SQL prompts like joins and second-highest salary, plus familiar ML questions such as bagging vs. boosting or LSTM, but the expectation was usually a high-level explanation rather than a research-level discussion. For analyst candidates, Power BI came up as a meaningful differentiator, especially around Desktop vs. Service, connection modes, gateways, and sharing reports externally. That tells us Infosys is checking whether you can operate in a client-facing, delivery-oriented environment where tools and communication matter as much as theory.

One non-obvious pattern: several candidates described the interviews as straightforward but somewhat uneven in depth, with some interviewers staying close to basics and others pushing a bit beyond the role title. That means the safest preparation is not memorizing obscure tricks, but being ready to defend every line on your resume and answer simple questions without hesitation. Candidates who sounded structured, specific, and comfortable under pressure generally came away better than those who overcomplicated answers or leaned on buzzwords.