Infosys Data Analyst Interview Preparation

The process usually runs through an online assessment into technical and HR interviews. The analyst track shifts the emphasis away from general programming and toward SQL and interpreting data, so weight your preparation toward those skills.

• Aptitude and reasoning: quantitative, logical, and verbal ability under time pressure.
• Technical assessment: SQL, spreadsheet logic, and data-interpretation questions.
• Technical interview: SQL querying, Excel or a BI tool, and reasoning about a dataset.
• HR interview: communication, motivation, and flexibility on location and role.

For analytics positions, expect emphasis on SQL and interpreting data rather than general software development. Interviewers care whether you can turn a dataset into a clear message a business reader could act on, which is the everyday work of the role. Serious Data Analyst / Data Science Jobs at Infosys reward candidates who verbalise trade-offs and edge cases aloud, not just producers of clean queries.

You can expect a recurring set of question types across the assessment and interview.

• SQL: joins, GROUP BY with aggregation, filtering with WHERE and HAVING, and basic window functions.
• Excel and BI: lookups, pivot tables, and summarising a dataset into a clear message.
• Statistics: mean, median, variance, and interpreting a trend or correlation.
• HR: tell me about yourself, why analytics, and why Infosys.

Take a SQL prompt: compute month-on-month growth in orders. A strong answer aggregates orders by month, uses a window function such as LAG to reference the previous month, computes the percentage change, and handles the first month where there is no prior value. When asked to interpret the trend, a strong candidate states what a sustained rise or fall would imply for the business and what confounder, such as a seasonal effect, they would rule out. Weak candidates write a query without checking duplicates or NULLs, or cannot say what a result means for the business, which is precisely where an interviewer decides whether you think like an analyst.

Criteria vary each cycle, so treat these as directional.

• Academics: Infosys commonly expects a consistent record around 60 percent or a specified CGPA, subject to the drive.
• Assessment score: a balanced performance across sections usually matters more than one strong area.
• SQL competence: writing and explaining correct joins and aggregations is a practical baseline.
• Communication: clear English often decides borderline cases.

Confirm current requirements from your placement cell or the official notification, as they shift per drive. For an analyst role, being able to explain a finding plainly is at least as important as the query itself, so make sure your preparation covers interpretation and not only syntax.

Structure preparation across the rounds so each stage gets attention.

• Aptitude: practise timed quantitative, logical and verbal sets.
• SQL: drill joins, aggregation, filtering and window functions, explaining each query aloud.
• Data interpretation: practise summarising datasets and stating what a trend implies for a decision.
• HR: rehearse your introduction and motivation until they flow naturally.

InterviewPrep's free AI voice mock interview is a useful final step: it builds a mock from your CV and the Infosys job description, listens to your spoken answers, and scores content, pace and filler words so your technical and HR delivery both land clearly. Rehearsing your interpretation of a dataset aloud, as though briefing a stakeholder, trains the plain-language explanation that Infosys analyst interviewers most want to hear.

Infosys analyst applicants repeatedly stumble on the same habits, and correcting them improves your standing across the rounds.

• Unvalidated queries: writing SQL without checking duplicates or NULLs yields results that fail under scrutiny.
• No interpretation: returning a number without saying what it means for the business misses the analyst's purpose.
• Ignoring the first period: mishandling the earliest month in a growth calculation, where no prior value exists, produces subtle errors.
• Weak spoken delivery: unclear explanations in the interview undercut sound analysis.

Validate your data, interpret each result plainly, and rehearse aloud, and you will present as a genuine analyst rather than only a query writer.