Is HireStepX free to use?

Yes. Start with 2 full AI mock interviews, complete with real-time feedback, scores, and detailed performance reports. No credit card required.

How does the AI mock interview work?

Upload your resume, pick your target company and role, and choose from 10 interview types. The AI interviewer asks role-specific questions via voice, listens to your answers, asks follow-up questions, and delivers scored feedback after each session.

What types of interviews can I practice?

10 types: Behavioral, Technical, Strategic, Case Study, Campus Placement, HR Round, Panel, Management, Salary Negotiation, and Government/PSU. Each with 3 difficulty levels and mini or full session options.

Can I practice for specific companies like TCS, Infosys, or Google?

Yes. We support 200+ target companies including Google, Amazon, TCS, Infosys, Flipkart, Razorpay, McKinsey, Deloitte, and more, each with distinct interview patterns.

How is this different from ChatGPT or practicing with friends?

ChatGPT is text-only with no voice, no scoring, no resume integration, and no progress tracking. HireStepX is a purpose-built interview simulator: voice-based, resume-personalized, with detailed analytics.

Is my interview data private and secure?

Yes. Data is encrypted via Supabase with row-level security. Recordings and transcripts are never shared with employers or third parties. Delete everything anytime from Settings.

Does HireStepX work on mobile?

Yes, on any modern browser. For the best experience during mock interviews, use a laptop or desktop with a microphone.

How much does it cost compared to a career coach?

A single coaching session typically costs ₹3,000-10,000. HireStepX is ₹9 per session or ₹39/month for 5 sessions (Sprint Pack) with full AI coaching and analytics, available 24/7.

What is the recruitment process at Flipkart?

The typical Flipkart recruitment process has 4 stages: Recruiter screen and SQL/coding pre-screen → SQL and data-manipulation round (window functions, joins) → Data pipeline and modelling design round → Hiring-manager and behavioural round, then offer.

What are the interview rounds at Flipkart?

Flipkart typically conducts 4 interview rounds: Round 1 (45-60 min): SQL screen on window functions, joins, and aggregation.; Round 2 (60 min): pipeline design round on batch and streaming ingestion with late-event handling.; Round 3 (45-60 min): data-modelling round on facts, dimensions, grain, and SCDs.; Round 4 (45 min): behavioural and hiring-manager round on ownership and collaboration..

What framework should I use for Flipkart technical interviews?

HireStepX recommends the Model-and-Aggregate framework for this type of interview: Show fluent window-function SQL, model facts and dimensions at the right grain, and reason about idempotent, late-event-tolerant aggregation for e-commerce analytics

Reverse a linked list in O(1) extra space. Then explain when you'd use this in production.

To answer this question well, HireStepX recommends the Model-and-Aggregate approach: Show fluent window-function SQL, model facts and dimensions at the right grain, and reason about idempotent, late-event-tolerant aggregation for e-commerce analytics Ground your answer in a specific real example from your own experience.

Given a large product catalogue, return the top-K best-selling items in a category efficiently as new sales stream in. Which data structure, and why?

To answer this question well, HireStepX recommends the Model-and-Aggregate approach: Show fluent window-function SQL, model facts and dimensions at the right grain, and reason about idempotent, late-event-tolerant aggregation for e-commerce analytics Ground your answer in a specific real example from your own experience.

Design and code an in-memory rate limiter or LRU cache for a product-detail service. Keep it clean, testable, and thread-safe.

To answer this question well, HireStepX recommends the Model-and-Aggregate approach: Show fluent window-function SQL, model facts and dimensions at the right grain, and reason about idempotent, late-event-tolerant aggregation for e-commerce analytics Ground your answer in a specific real example from your own experience.

Given delivery slots and orders, assign orders to slots to maximise fulfilment without overbooking any slot. Walk through your approach and complexity.

To answer this question well, HireStepX recommends the Model-and-Aggregate approach: Show fluent window-function SQL, model facts and dimensions at the right grain, and reason about idempotent, late-event-tolerant aggregation for e-commerce analytics Ground your answer in a specific real example from your own experience.

Write a SQL query to find, for each product category, the top 3 sellers by revenue in the last 30 days, handling ties consistently.

To answer this question well, HireStepX recommends the Model-and-Aggregate approach: Show fluent window-function SQL, model facts and dimensions at the right grain, and reason about idempotent, late-event-tolerant aggregation for e-commerce analytics Ground your answer in a specific real example from your own experience.

Design a batch and streaming pipeline that ingests clickstream events and produces near-real-time category-level conversion metrics. How do you handle late-arriving events?

To answer this question well, HireStepX recommends the Model-and-Aggregate approach: Show fluent window-function SQL, model facts and dimensions at the right grain, and reason about idempotent, late-event-tolerant aggregation for e-commerce analytics Ground your answer in a specific real example from your own experience.

How would you model an orders fact table and its dimensions for an analytics warehouse serving both finance and category teams? Discuss grain and slowly changing dimensions.

To answer this question well, HireStepX recommends the Model-and-Aggregate approach: Show fluent window-function SQL, model facts and dimensions at the right grain, and reason about idempotent, late-event-tolerant aggregation for e-commerce analytics Ground your answer in a specific real example from your own experience.

Design an ML system to predict delivery delays at order time. What features, model, and feedback loop would you use, and how do you avoid stale predictions?

To answer this question well, HireStepX recommends the Model-and-Aggregate approach: Show fluent window-function SQL, model facts and dimensions at the right grain, and reason about idempotent, late-event-tolerant aggregation for e-commerce analytics Ground your answer in a specific real example from your own experience.

What SQL does Flipkart ask data engineers?

Window functions are central: top-N sellers per category, running and week-over-week metrics, deduplication, and correct tie-handling with ROW_NUMBER, RANK, and LAG.

What pipeline questions does Flipkart ask?

Designing batch and streaming pipelines for clickstream and order data, handling late-arriving events with watermarking, and producing idempotent near-real-time conversion metrics.

Does Flipkart test data modelling?

Yes. Expect dimensional modelling: fact-table grain, star schema, and slowly changing dimensions (SCD type-2) for an analytics warehouse serving multiple teams.

← All companies·Flipkart·Technical

Flipkart Data Engineer Interview Questions India 2026

Flipkart's data-engineering interviews test SQL depth, pipeline design, and dimensional modelling at e-commerce scale.

Practice with AI voice feedback 10 questions · Technical · 2 sessions free

In 2026 expect a SQL screen heavy on window functions (top-N sellers per category, running metrics, tie-handling), a pipeline round on ingesting clickstream events into near-real-time conversion metrics with late-event handling, and a data-modelling round on orders fact tables, grain, and slowly changing dimensions. Flipkart's data org powers pricing, category, and finance analytics, so interviewers reward engineers who reason about correctness of aggregates, idempotency of reloads, and the batch-versus-streaming trade-off rather than reciting tool names. Ground every answer in a real e-commerce analytics workflow.

About Flipkart

Indian e-commerce major (Walmart-owned since 2018); horizontal marketplace + private brands + grocery + fashion via Myntra.

Products: Flipkart marketplace · Myntra (fashion) · Flipkart Grocery · Cleartrip (travel) · Shopsy (reseller)
Competitors: Amazon India · Meesho · Reliance Retail (JioMart) · Tata Neu
Scale: Hundreds of millions of registered users. India's largest e-commerce marketplace by GMV. Walmart-owned, IPO discussions ongoing.

Flipkart recruitment process

01
Recruiter screen and SQL/coding pre-screen
02
SQL and data-manipulation round (window functions, joins)
03
Data pipeline and modelling design round
04
Hiring-manager and behavioural round, then offer

What to expect in each round

01
Round 1 (45-60 min)
SQL screen on window functions, joins, and aggregation.
02
Round 2 (60 min)
pipeline design round on batch and streaming ingestion with late-event handling.
03
Round 3 (45-60 min)
data-modelling round on facts, dimensions, grain, and SCDs.
04
Round 4 (45 min)
behavioural and hiring-manager round on ownership and collaboration.

Technical questions Flipkart asked

Sourced from 2+ candidate post-mortems. Hit Practice to answer any one with AI voice feedback.

01
Medium
Reverse a linked list in O(1) extra space. Then explain when you'd use this in production.
Practice free →
02
Hard
Given a large product catalogue, return the top-K best-selling items in a category efficiently as new sales stream in. Which data structure, and why?
Practice free →
03
Hard
Design and code an in-memory rate limiter or LRU cache for a product-detail service. Keep it clean, testable, and thread-safe.
Practice free →
04
Medium
Given delivery slots and orders, assign orders to slots to maximise fulfilment without overbooking any slot. Walk through your approach and complexity.
Practice free →
05
Medium
Write a SQL query to find, for each product category, the top 3 sellers by revenue in the last 30 days, handling ties consistently.
Practice free →
06
Hard
Design a batch and streaming pipeline that ingests clickstream events and produces near-real-time category-level conversion metrics. How do you handle late-arriving events?
Practice free →
07
Medium
How would you model an orders fact table and its dimensions for an analytics warehouse serving both finance and category teams? Discuss grain and slowly changing dimensions.
Practice free →
08
Hard
Design an ML system to predict delivery delays at order time. What features, model, and feedback loop would you use, and how do you avoid stale predictions?
Practice free →
09
Medium
A pricing model performs well in offline tests but underperforms live. List the likely reasons and how you'd investigate each.
Practice free →
10
Hard
How would you design an A/B test for a new ranking model when network effects mean one user's experience affects another's?
Practice free →

Reading won't get you hired

Stop reading, start answering.

The AI asks Flipkart-style questions, listens to your voice, and scores your answer in two minutes. 2 sessions free, no card.

Start free practice

← All companies·Flipkart·Technical

Flipkart Data Engineer Interview Questions India 2026

Flipkart's data-engineering interviews test SQL depth, pipeline design, and dimensional modelling at e-commerce scale.

Practice with AI voice feedback 10 questions · Technical · 2 sessions free

About Flipkart

Indian e-commerce major (Walmart-owned since 2018); horizontal marketplace + private brands + grocery + fashion via Myntra.

Products: Flipkart marketplace · Myntra (fashion) · Flipkart Grocery · Cleartrip (travel) · Shopsy (reseller)
Competitors: Amazon India · Meesho · Reliance Retail (JioMart) · Tata Neu
Scale: Hundreds of millions of registered users. India's largest e-commerce marketplace by GMV. Walmart-owned, IPO discussions ongoing.

Flipkart recruitment process

01
Recruiter screen and SQL/coding pre-screen
02
SQL and data-manipulation round (window functions, joins)
03
Data pipeline and modelling design round
04
Hiring-manager and behavioural round, then offer

What to expect in each round

01
Round 1 (45-60 min)
SQL screen on window functions, joins, and aggregation.
02
Round 2 (60 min)
pipeline design round on batch and streaming ingestion with late-event handling.
03
Round 3 (45-60 min)
data-modelling round on facts, dimensions, grain, and SCDs.
04
Round 4 (45 min)
behavioural and hiring-manager round on ownership and collaboration.

Technical questions Flipkart asked

Sourced from 2+ candidate post-mortems. Hit Practice to answer any one with AI voice feedback.

01
Medium
Reverse a linked list in O(1) extra space. Then explain when you'd use this in production.
Practice free →
02
Hard
Given a large product catalogue, return the top-K best-selling items in a category efficiently as new sales stream in. Which data structure, and why?
Practice free →
03
Hard
Design and code an in-memory rate limiter or LRU cache for a product-detail service. Keep it clean, testable, and thread-safe.
Practice free →
04
Medium
Given delivery slots and orders, assign orders to slots to maximise fulfilment without overbooking any slot. Walk through your approach and complexity.
Practice free →
05
Medium
Write a SQL query to find, for each product category, the top 3 sellers by revenue in the last 30 days, handling ties consistently.
Practice free →
06
Hard
Design a batch and streaming pipeline that ingests clickstream events and produces near-real-time category-level conversion metrics. How do you handle late-arriving events?
Practice free →
07
Medium
How would you model an orders fact table and its dimensions for an analytics warehouse serving both finance and category teams? Discuss grain and slowly changing dimensions.
Practice free →
08
Hard
Design an ML system to predict delivery delays at order time. What features, model, and feedback loop would you use, and how do you avoid stale predictions?
Practice free →
09
Medium
A pricing model performs well in offline tests but underperforms live. List the likely reasons and how you'd investigate each.
Practice free →
10
Hard
How would you design an A/B test for a new ranking model when network effects mean one user's experience affects another's?
Practice free →

Reading won't get you hired

Stop reading, start answering.

The AI asks Flipkart-style questions, listens to your voice, and scores your answer in two minutes. 2 sessions free, no card.

Start free practice