Data Analyst Interview Questions for Indian Firms 2026

Indian data analyst interviews across companies like Flipkart, Swiggy, Razorpay, and TCS typically cover four core areas in roughly this proportion.

• SQL (40–50%): JOINs, window functions, aggregations, CTEs: the biggest filter
• Statistics and probability (15–20%): mean vs median, distributions, A/B testing basics
• Python or Excel (15%): Pandas for data wrangling; Excel/Sheets for business analyst roles
• Business case and problem-solving (20–30%): 'How would you measure the success of Feature X?'
• Communication: can you explain a finding to a non-technical stakeholder clearly?

SQL is the make-or-break skill. Most Indian DA interviews include a live SQL coding exercise on platforms like HackerRank or a shared Google Doc.

• 'Find the second highest salary in each department': tests window functions (RANK/DENSE_RANK)
• 'Monthly active users who were also active last month': tests self-JOINs and date functions
• 'Running total of revenue by day': tests SUM() OVER (ORDER BY date)
• 'Find customers who bought product A but not B': tests NOT IN vs LEFT JOIN IS NULL
• Always write readable SQL with aliases and formatting: interviewers score readability

You do not need a statistics degree, but you do need to know the fundamentals cold.

• When to use mean vs median: median for skewed distributions (income, session length)
• Standard deviation vs variance: know the formula and when each is more useful
• A/B testing: null hypothesis, p-value interpretation, Type I vs Type II error
• Correlation vs causation: this comes up as a business case ('DAU went up, revenue went down: why?')
• Common interview question: 'Sample sizes are different in your A/B test: is it still valid?'

Business case questions separate analysts from data operators. Companies like Swiggy, Zomato, and Razorpay use these heavily to assess thinking quality.

• Step 1: Clarify the goal: 'What business outcome are we trying to improve?'
• Step 2: Break down the metric: DAU = New users + Retained users – Churned users
• Step 3: Form hypotheses: internal (product changes) vs external (market, seasonality)
• Step 4: Define what data you would look at and what a meaningful change looks like
• Practice question: 'Swiggy's average order value dropped 12% in Tier-2 cities last month: diagnose.'

For product company DA roles, Python is increasingly tested. Focus on data manipulation with Pandas, not machine learning.

The interview flavour varies significantly between service IT, Indian product unicorns, and early-stage startups.

• TCS/Infosys DA roles: heavier on Excel, SQL basics, and report automation: less business case
• Flipkart/Swiggy/Zomato: strong business case focus, some Python, and metric definition questions
• Fintech (Razorpay/PhonePe): payments domain knowledge + cohort analysis + funnel metrics
• Early-stage startups: expect to be asked to build a dashboard end-to-end in the interview
• Across all: prepare a 2-minute story of 'a project where your analysis changed a decision'