Swiggy Business Analyst Interview Questions + Guide in 2025

Swiggy is India’s leading on-demand delivery platform, operating in over 500 cities with a tech-driven logistics model and a strong partner network.

As a Business Analyst at Swiggy, you’ll drive strategic initiatives and operational efficiency through data. Your responsibilities include building dashboards to monitor business metrics, analyzing data to improve conversion rates, managing P&L for partnerships, and coordinating growth projects across cities. You’ll work cross-functionally to translate insights into action.

Key skills include SQL, Excel, and a solid foundation in statistics and probability. Swiggy values candidates who thrive in ambiguity, take ownership, and communicate clearly across teams.

This guide will help you prepare by outlining the role expectations and common interview questions—so you can demonstrate your skills and align with Swiggy’s data-first culture.

Swiggy’s Business Analyst interview process is designed to evaluate technical skills, analytical thinking, and business judgment. The process typically consists of multiple rounds, each focusing on a core competency relevant to the role.

3.1 Initial Screening

The process begins with a recruiter screening, where your resume is reviewed and you’ll have a brief conversation about your background, interest in the role, and understanding of Swiggy’s business. This stage sets expectations for the upcoming rounds.

3.2 Technical Assessment

Next is an online technical assessment, often conducted via platforms like HackerEarth or HackerRank. It usually includes SQL questions ranging from basic to advanced, testing your ability to manipulate and interpret data. Some assessments also feature a business case to gauge problem-solving and real-world thinking.

As one candidate recalled, “The first round is a HackerEarth assessment with 8 questions on SQL—it’s a mix of query writing and analytical reasoning.”

3.3 Technical Interview

This round focuses on SQL proficiency, statistics, and core analytical skills. You may be asked to write queries, explain statistical concepts, or apply them in business contexts.

According to one interviewee, “My technical round had questions on SQL execution order, window functions, and statistical reasoning like confidence intervals and hypothesis testing.”

3.4 Business Case Study

You’ll be presented with a case study relevant to Swiggy’s business—often involving growth, retention, or operations. You’ll need to identify metrics, analyze root causes, and propose actionable strategies. Clear communication and structured thinking are key.

One candidate shared, “I had to do root cause analysis on a revenue drop, estimate AC sales in India, and define KPIs for a product feature—it was quite comprehensive.”

3.5 Hiring Manager Interview

The final round is with the hiring manager and may include a mix of behavioral, strategic, and follow-up questions. You’ll discuss past projects, team fit, and long-term goals.

As one interviewee noted, “The hiring manager round was a mix of project discussions, behavioral questions, and follow-ups on previous case rounds.”

Here are key tips to help you stand out during the Swiggy Business Analyst interview process.

4.1 Understand the Interview Structure

The process typically includes several rounds: an initial SQL assessment, followed by interviews focused on statistics, business case studies, and discussions with hiring managers. Familiarizing yourself with the structure will help you manage your time and expectations effectively.

As one candidate noted, “It was a quick process that spanned 8–9 days—the HR support was great, and each round was well communicated.”

4.2 Master SQL and Data Analysis

SQL is core to the role. Practice writing advanced queries with joins, subqueries, and window functions. Focus on clarity, performance, and real-world data problems. Proficiency in Excel—particularly for dashboarding and reporting—is also critical for success in day-to-day analyst work.

4.3 Prepare for Business Case Studies

You’ll likely be asked to solve case studies involving growth metrics, retention issues, or operational challenges. Practice breaking down open-ended problems and presenting structured, metric-driven recommendations. Understanding Swiggy’s business model and customer segments will help you contextualize your answers.

4.4 Hone Your Problem-Solving Skills

Expect guesstimates and ambiguous analytical scenarios. Interviewers are less interested in perfect answers and more focused on how you frame problems, make assumptions, and justify trade-offs. Clearly explain your approach and decision-making process.

4.5 Showcase Communication Skills

Business Analysts at Swiggy interact with stakeholders across product, ops, and leadership teams. During the interview, demonstrate that you can explain complex insights simply and clearly. Ask clarifying questions, communicate your reasoning, and connect your analysis to business impact.

4.6 Align with Company Culture

Swiggy’s culture is fast-moving and innovation-driven. Highlight examples where you’ve taken ownership, adapted quickly, or contributed to process improvements. Show that you’re comfortable with ambiguity and capable of thriving in a dynamic environment.

4.7 Follow Up Professionally

After the interview, send a thank-you email to express appreciation and reinforce your interest. This small gesture reflects professionalism and helps keep you top-of-mind as hiring decisions are made.

With thorough preparation and a clear understanding of what Swiggy values, you’ll be well-positioned to succeed in your Business Analyst interview. Good luck!

In this section, we’ll review common interview questions asked for the Business Analyst role at Swiggy. The interview process assesses your technical proficiency, analytical thinking, and business judgment. Be prepared to showcase your skills in SQL, statistics, and applied problem-solving.

5.1 SQL and Data Analysis

5.1.1 Can you explain the difference between INNER JOIN and LEFT JOIN in SQL?

Understanding joins is foundational for working with relational data.

How to Answer

Clearly define both joins and explain a relevant use case for each.

Example

“An INNER JOIN returns only rows with matching keys in both tables, while a LEFT JOIN returns all rows from the left table and the matching records from the right. For example, joining a customer table with an orders table—an INNER JOIN shows customers with orders, while a LEFT JOIN includes all customers, even those without any orders.”

5.1.2 How would you write a SQL query to find the top 5 products by sales?

This tests your ability to write efficient, business-relevant queries.

How to Answer

Walk through how you would use aggregation (SUM), sorting (ORDER BY), and limiting (LIMIT).

Example

“I’d group the data by product, sum the sales, sort by total sales in descending order, and limit the results to five rows. The query would include: SELECT product_id, SUM(sales) AS total_sales FROM sales_table GROUP BY product_id ORDER BY total_sales DESC LIMIT 5.”

5.1.3 Describe a situation where you had to clean a dataset. What steps did you take?

Data quality is crucial for reliable analysis.

How to Answer

Share the types of issues you encountered, such as null values, duplicates, or inconsistent formats, and describe how you addressed them.

Example

“I worked with a dataset that had missing values and duplicates. I identified nulls and filled them using the column mean where appropriate. For duplicates, I used DISTINCT and filtering techniques to retain only the most recent records. These steps helped ensure the analysis was based on clean, consistent data.”

5.1.4 What is a rolling sum in SQL, and how would you implement it?

This tests your understanding of window functions—commonly used in time-based analysis.

How to Answer

Explain the concept of a rolling or cumulative sum and how window functions like OVER with an appropriate frame clause are used.

Example

“A rolling sum calculates the cumulative total up to the current row in a dataset. I would use the SUM function along with the OVER clause, ordering by date, and define the window as all previous rows including the current one. This helps in trend and performance tracking over time.”

5.1.5 How do you handle outliers in a dataset?

Swiggy values analysts who can handle messy, real-world data responsibly.

How to Answer

Mention how you detect outliers using statistical techniques, and explain your approach to deciding whether to remove or retain them.

Example

“I typically use the Z-score or interquartile range (IQR) to detect outliers. If an outlier is the result of a clear data entry error—like a negative order value—I remove it. But if it’s a valid but extreme value, such as a very large transaction, I may retain it and analyze its influence separately or apply a transformation depending on the use case.”

5.2 Statistics and Probability

5.2.1 Explain the concept of hypothesis testing

This question evaluates your grasp of statistical inference.

How to Answer

Define hypothesis testing and explain its role in drawing conclusions from data.

Example

“Hypothesis testing is a statistical method used to determine whether a given assumption about a dataset (the null hypothesis) can be rejected. It involves setting up null and alternative hypotheses, choosing a significance level, calculating a test statistic, and comparing it to a critical threshold to decide whether the null hypothesis holds.”

5.2.2 What is the difference between Type I and Type II errors?

Understanding these errors is key to evaluating test results accurately.

How to Answer

Clearly define each error and explain the trade-off between them with an example.

Example

“A Type I error occurs when we incorrectly reject a true null hypothesis—a false positive. A Type II error happens when we fail to reject a false null hypothesis—a false negative. For instance, if a website test shows no improvement but actually does boost conversions, that’s a Type II error.”

5.2.3 Can you describe a scenario where you used A/B testing?

A/B testing is often used to validate product or process changes.

How to Answer

Describe how you structured the test, what metrics you tracked, and what the outcome was.

Example

“I ran an A/B test to evaluate a new checkout page layout. Users were randomly assigned to either the current version or the test version. After two weeks, the new layout showed a 15% increase in conversion rate, which was statistically significant, so we rolled it out sitewide.”

5.2.4 How do you determine the sample size for a study?

Sample size impacts the reliability and power of your conclusions.

How to Answer

Explain the core factors—confidence level, margin of error, and population variability—that influence sample size.

Example

“I consider the desired confidence level, margin of error, and estimated population proportion. For example, increasing the confidence level or reducing the margin of error would require a larger sample. I typically use statistical calculators or formulas that factor in these variables to estimate the required sample size.”

5.2.5 What is the Central Limit Theorem?

A fundamental concept for anyone working with sampling and distributions.

How to Answer

Define the theorem and explain its practical significance in data analysis.

Example

“The Central Limit Theorem states that as the sample size increases, the sampling distribution of the sample mean will approach a normal distribution, even if the population distribution is not normal. This allows us to use normal distribution-based methods like confidence intervals and hypothesis tests, even when working with non-normal data.”

5.3 Business Acumen and Problem Solving

5.3.1 How would you approach a business problem where sales have dropped?

This question evaluates your structured thinking and ability to diagnose real-world business issues.

How to Answer

Walk through a logical approach—from identifying the problem to proposing potential solutions.

Example

“I would start by analyzing sales data over time, segmented by product, region, and channel to pinpoint where the drop occurred. I’d then investigate external factors like seasonality or competition and gather qualitative inputs from customer feedback or support tickets. Based on these insights, I’d recommend targeted actions—like adjusting pricing, refining marketing campaigns, or improving product features—to address the root cause.”

5.3.2 Describe a time when you had to present complex data to a non-technical audience

Effective communication is essential for influencing stakeholders.

How to Answer

Share how you simplified complex findings using visuals or storytelling and ensured clarity.

Example

“I presented a customer retention analysis to the marketing team. To simplify the data, I used charts and dashboards that focused on key patterns rather than raw numbers. I emphasized actionable takeaways and tied them directly to campaign strategies, which helped the team quickly grasp the insights and adjust their messaging.”

5.3.3 How do you prioritize tasks when managing multiple projects?

This tests your ability to manage time and resources in a high-growth environment.

How to Answer

Discuss the framework or tools you use and how you balance urgency with impact.

Example

“I prioritize based on business impact and deadlines. I use a matrix to rank tasks by urgency and importance, then schedule my work accordingly. Tools like Trello help me stay organized, and I reassess priorities weekly to stay aligned with shifting goals.”

5.3.4 What metrics would you track to measure the success of a new feature?

Swiggy values data-driven decision-making—this question checks for KPI fluency.

How to Answer

Name relevant metrics and explain how they align with business objectives.

Example

“I’d track metrics like adoption rate, user engagement, retention, and feature-specific conversions. If it’s a customer-facing feature, I’d also look at Net Promoter Score or support ticket volume to understand sentiment and usability. Together, these help assess both performance and user satisfaction.”

5.3.5 How would you identify city-level opportunities for growth?

This checks your ability to think strategically about geographic expansion.

How to Answer

Describe the data inputs and methods you’d use to evaluate market potential.

Example

“I’d analyze city-level data on order volume, customer acquisition costs, and partner availability. I’d also review market demographics and competitor presence to spot underserved areas. Combining internal performance metrics with external market trends would allow me to build a data-backed expansion plan.”

Preparing for the Swiggy Business Analyst interview means going beyond just technical proficiency—it’s about showing you can think critically, solve business problems, and communicate insights that drive action. By mastering SQL, refining your problem-solving approach, and aligning with Swiggy’s fast-paced, customer-focused culture, you’ll position yourself as a strong candidate. With the right preparation, you won’t just answer questions—you’ll demonstrate that you’re ready to make an impact from day one.