Assessment tips
- Confirm the current Ola pattern from the drive mail before practising old papers
- Finish one problem or section fully before starting the next
- Revise the fundamentals listed in the round table on this page
Ola Interview Experience 2026
How Ola fresher SDE interviews usually run, synthesized from campus and off-campus reports. We reorganized OA → DSA/design technicals → values managerial → HR - treat this as a prep map, not a script.
Ola placement process 2026 (from student reports) includes: 1. Online Coding Assessment (OA): 90-120 minutes with 2-3 DSA problems and debugging questions on HackerRank, 2. Technical Interviews (2-3 rounds, 45-60 min each) covering DSA, coding, and system design (ride matching, payments), 3. Managerial/Team Fit Interview (45 min) focusing on Ola values (customer focus, innovation, ownership), 4. HR/Offer Discussion (20-30 min). Total duration: 2-4 weeks from application to offer.
Eligibility (from student reports): 6.5+ CGPA in 10th, 12th, and graduation.
Fresher package ballpark (from student reports): SDE-1: ₹16-22 LPA. Confirm on your offer letter.
Round-wise process
| Round | Duration | What they test |
|---|---|---|
| Online Assessment | 90-120 min | 2-3 coding problems (DSA) |
| Technical Round 1 | 45-60 min | DSA + detailed project discussion |
| Technical Round 2 | 45-60 min | DSA / system design basics |
| Hiring Manager / HR | 30-45 min | Behavioural + team fit |
Real interview experiences
Technical interview experience 1
Candidate Background: B.Tech Computer Science, 8.2 CGPA, 2 internships in backend development, strong DSA skills
Round 1 - Online Assessment (OA)
Experience: The OA was conducted on HackerRank with 3 coding problems:
- Array Problem: Find maximum sum subarray (Kadane’s algorithm variant)
- Tree Problem: Find lowest common ancestor in a binary tree
- Graph Problem: Shortest path in a weighted graph (Dijkstra’s algorithm)
Time Allocated: 120 minutes
Approach: I solved all 3 problems correctly, focusing on optimal time complexity. The debugging section had 2 questions where I had to identify and fix bugs in provided code.
Result: Cleared OA, advanced to technical interviews
Round 2 - Technical Interview 1 (60 minutes)
Questions Asked:
- Started with “Tell me about yourself” and project discussion
- Coding Problem: Design a data structure to support insert, delete, and getRandom in O(1) time
- Follow-up: Optimize for space complexity
- System Design: Design a ride matching system for Ola
Approach:
- Explained my approach clearly before coding
- Used HashMap + ArrayList for the data structure problem
- Discussed trade-offs and edge cases
- For system design, covered scalability, load balancing, database design, real-time matching
Result: Positive feedback, advanced to next round
Round 3 - Technical Interview 2 (45 minutes)
Questions Asked:
- Coding Problem: Implement LRU Cache with O(1) operations
- Algorithm Discussion: Explain Dijkstra’s algorithm and when to use it
- System Design: Design a payment gateway with transaction safety
- Project Deep Dive: Detailed discussion on my internship project
Approach:
- Implemented LRU using HashMap + Doubly Linked List
- Explained algorithm complexity and use cases
- Discussed ACID properties, idempotency, retry mechanisms for payment system
- Walked through project architecture and design decisions
Result: Strong performance, advanced to managerial round
Round 4 - Managerial/Team Fit Interview (45 minutes)
Questions Asked:
- Ola Values: “Describe a time you demonstrated ownership”
- Scenario: “How would you handle a production issue at 2 AM?”
- Teamwork: “Describe a conflict you resolved in a team”
- Technical Discussion: Architecture decisions, trade-offs in system design
Approach:
- Used STAR format for behavioral questions
- Emphasized customer focus and ownership
- Discussed on-call responsibilities and incident management
- Showed alignment with Ola’s values
Result: Cultural fit confirmed, advanced to HR round
Round 5 - HR Interview (30 minutes)
Questions Asked:
- Personal background and education
- “Why Ola?”
- Salary expectations
- Joining date and relocation
- Questions about Ola’s culture and growth
Result: Selected - Received offer for SDE-1 role with ₹18 LPA package
Tips:
- Strong DSA preparation is crucial
- Practice system design problems relevant to mobility tech
- Be ready to discuss Ola’s business model and technology
- Demonstrate alignment with Ola’s values
Takeaways
- What decided it: Full OA (Kadane/LCA/Dijkstra + debugging), O(1) random-set + ride-matching design, LRU/payment safety, and Ola-values STAR ownership
- Common fail: Generic mobility design without matching/dispatch trade-offs; soft values answers without incidents
- How to practise: Timed 3-problem + debug mocks; HashMap+ArrayList random set; ride matching + idempotent payments aloud
Technical interview experience 2
Candidate Background: M.Tech Computer Science, 8.5 CGPA, 1 year experience in a product company, expertise in distributed systems
Round 1 - Online Assessment (OA)
Experience: OA had 2 medium-hard coding problems:
- Dynamic Programming: Coin change problem variant
- Graph Algorithm: Detect cycle in directed graph and find all cycles
Solved both problems optimally. Debugging section was straightforward.
Result: Cleared OA
Round 2 - Technical Interview 1 (60 minutes)
Questions Asked:
- Coding: Implement a rate limiter (sliding window algorithm)
- System Design: Design Ola’s real-time location tracking system
- Discussion: Microservices architecture, event-driven systems
Approach:
- Implemented rate limiter using circular buffer
- Designed location tracking with WebSockets, Redis for caching, Kafka for events
- Discussed scalability, fault tolerance, data consistency
Result: Advanced to next round
Round 3 - Technical Interview 2 (60 minutes)
Questions Asked:
- Coding: Design a distributed cache system (coding + architecture)
- System Design: Design Ola’s surge pricing system
- Discussion: CAP theorem, eventual consistency, database sharding
Approach:
- Discussed cache eviction policies, consistency models
- Designed surge pricing with real-time demand calculation, pricing algorithms
- Explained trade-offs between consistency and availability
Result: Advanced to managerial round
Round 4 - Managerial Interview (45 minutes)
Questions Asked:
- Leadership experience and handling ambiguity
- Technical decision-making in previous role
- “How do you stay updated with technology?”
- Discussion on Ola’s technology roadmap
Result: Advanced to HR round
Round 5 - HR Interview (25 minutes)
Questions Asked:
- Why leaving current company?
- Why Ola?
- Salary negotiation
- Joining timeline
Result: Selected - Received offer for SDE-2 role with ₹26 LPA package
Tips:
- System design knowledge is crucial for experienced candidates
- Be ready to discuss distributed systems, scalability
- Show interest in Ola’s technology and business
Takeaways
- What decided it: Distributed-systems depth and scalability talk for experienced/M.Tech profiles, plus interest in Ola tech/business
- Common fail: Fresher-only DSA prep when the panel expects system-design ownership
- How to practise: Ride-matching at scale; payment safety (ACID/idempotency); one production incident STAR
Technical interview experience 3 (experienced SDE-1 backend)
Candidate Background: ~2 YOE backend engineer, applied via recruiter for Bengaluru SDE-1; composite from public 2024-2025 reports (Medium, GeeksforGeeks)
Round 1 - DSA (virtual)
Questions Asked:
- Two-sum style array problem (hashing vs sorting discussed)
- Puzzle follow-up: ages of three children with product 72 and sum 14 - interviewer wanted one answer with reasoning (candidates debate [2,6,6] vs [3,3,8])
Approach: Talked through constraints before coding; clarified ambiguous puzzle wording.
Result: Advanced to design round
Round 2 - High-Level Design (~60 min)
Questions Asked:
- Design a URL shortening service (not ride-hailing - some lateral loops use generic HLD)
- Short-code length, DB choice, cache layer, eviction policy, write-through vs write-back
- TTL / cleanup for expired URLs; extension to click analytics
Approach: Separated read path (cache + DB) from write path; async aggregation for analytics.
Result: Advanced to hiring-manager round
Round 3 - Hiring Manager
Questions Asked:
- Current role responsibilities
- SOLID principles with small code examples
- Culture and ownership scenarios
Result: Outcome varied by candidate - reports stress HM depth even when coding was strong
HR interview experience
Candidate Background: B.Tech IT, 7.8 CGPA, Final year student, strong communication skills
HR Interview (30 minutes)
Questions Asked:
- “Tell me about yourself”
- “Why do you want to join Ola?”
- “What do you know about Ola’s business?”
- “Describe a time you worked under pressure”
- “Where do you see yourself in 5 years?”
- “Are you willing to relocate to Bengaluru?”
- “What are your salary expectations?”
- “Do you have any questions for us?”
Approach:
- Researched Ola’s business model, technology, and recent developments
- Prepared STAR stories for behavioral questions
- Showed enthusiasm for mobility tech and AI
- Asked thoughtful questions about team structure and growth opportunities
Result: Selected - Received offer for SDE-1 role
Tips:
- Research the company thoroughly
- Prepare specific examples using STAR format
- Show genuine interest in the company and role
- Ask intelligent questions about the company
Questions that come up often
Coding / technical
- Longest substring without repeating characters. Usually expects sliding window + hashmap
- Binary tree level order traversal. Usually expects BFS
- Detect cycle in a directed graph. Usually expects DFS colouring / topological sort
- Merge k sorted arrays or ticket-queue simulation (OA reports)
- Discussion on ride matching and surge pricing, bottlenecks, failure modes, simple APIs
- URL shortener or notification-system HLD on some backend tracks
- Detailed project discussion, architecture, hardest bug, what you would change
HR / behavioural
- Why this company?
- A disagreement with a teammate and how you handled it
- An ownership example from a project
- Relocation preference
Practical tips for Ola
- Clear the screening round first. Timed practice beats last-minute topic hopping.
- For domain questions, explain ride matching in plain language, inputs, outputs, what breaks at scale.
- OOPs and SQL still open a lot of Ola panels. Do not skip fundamentals.
- HR answers should be concrete. One story with a result beats five slogans.
- If you do not know something, say so and outline how you would find out.
HR interview
After technical rounds, Ola usually closes with a short HR / hiring-manager conversation: motivation, location, notice period, and a couple of behavioural stories. Prepare those answers on the dedicated page rather than cramming them into this hub.
Sample answers for high-frequency questions
Use these as frames, not scripts - interviewers probe follow-ups.
Q. Explain Kadane’s algorithm for maximum-sum subarray and its complexity.
A. Kadane’s algorithm makes a single pass, maintaining current_sum = max(num, current_sum + num) at each index and best = max(best, current_sum). The insight is that a prefix with a negative running sum can never help a later subarray, so you discard it and restart at the current element. Time is O(n) and space is O(1). If all elements are negative, initialise best to the first element rather than 0, otherwise you incorrectly return 0 for a non-empty array.
Q. How do you find the lowest common ancestor of two nodes in a binary tree?
A. For a general binary tree, recurse from the root: if the current node is null or equals either target, return it. Recurse left and right; if both sides return non-null, the current node is the LCA, otherwise return whichever side is non-null. This is O(n) time and O(h) space for the recursion stack, where h is the tree height. In a binary search tree you can do better - walk down from the root and the first node whose value lies between the two targets is the LCA, which is O(h) time and O(1) space iteratively.
Q. How does Dijkstra’s algorithm work, and when does it fail?
A. Dijkstra maintains a distance array initialised to infinity except the source at 0, and repeatedly extracts the unvisited node with the smallest known distance from a min-heap, relaxing each outgoing edge by checking whether dist[u] + weight(u,v) improves dist[v]. With a binary heap it runs in O((V + E) log V). It fails on graphs with negative edge weights, because once a node is finalised it is never revisited - use Bellman-Ford (O(VE)) there instead. For road-network routing like Ola’s ETA problem, A with a geographic heuristic is the practical refinement.
Q. Design a data structure supporting insert, delete, and getRandom in O(1).
A. Combine a dynamic array (list) with a hash map from value to that value’s index in the array. Insert appends to the array and records the index in the map. Delete looks up the index, swaps that element with the last element of the array, updates the swapped element’s index in the map, pops the array tail, and erases the key. getRandom picks a uniform random index into the array. Every operation is O(1) average, and the swap-with-last trick is what avoids the O(n) shift a naive array removal would cost.
Q. How do you implement an LRU cache, and why those specific data structures?
A. Use a hash map from key to node plus a doubly linked list ordered most-recently-used at the head and least-recently-used at the tail. On get, look up the node in O(1) and move it to the head. On put, insert at the head, and if size exceeds capacity, remove the tail node and delete its key from the map. The doubly linked list is required because removing an arbitrary node in O(1) needs both prev and next pointers; a singly linked list would force an O(n) scan to find the predecessor. Both operations are O(1) with O(capacity) space.
Tips from successful candidates
Interview tips
- Narrate trade-offs; expect “why” after every answer
- Only list projects you can defend under follow-ups
- Prepare 3-4 STAR stories for behavioural prompts
HR tips
- Know why Ola, not just why the industry
- Be clear on location / notice period / higher studies
- Practise answers on the dedicated HR page
Sources
Round-wise notes on this page are curated from public candidate reports, then reorganized with prep takeaways and outcome context on GeeksforGeeks, Ola SDE-1 experience (Medium), and aggregated 2025 patterns on placementpapers.app. Cross-check the current drive mail for timings - Ola Electric campus loops are a separate employer from mobility Ola even when branding overlaps.