Study Materials - Freshershunt

🎯 EY Java Backend Developer Interview — Important Questions Preparing for a Java Backend Developer interview at EY? Don't prepare only DSA. Core Java, Spring Boot, SQL, and System Design are equally important. 👇 🔥 𝗥𝗢𝗨𝗡𝗗 𝟭 — 𝗖𝗢𝗥𝗘 𝗝𝗔𝗩𝗔 & 𝗗𝗦𝗔 🔹 How does HashMap work internally? 🔹 Why should equals() and hashCode() be overridden together? 🔹 HashMap vs ConcurrentHashMap 🔹 Why is String immutable in Java? 🔹 Interface vs Abstract Class 🔹 Find the longest substring without repeating characters. 🔹 Find the first non-repeating character in a string. 🔹 Merge overlapping intervals. 🔹 Find the Top K frequent elements. 🔥 𝗥𝗢𝗨𝗡𝗗 𝟮 — 𝗠𝗨𝗟𝗧𝗜𝗧𝗛𝗥𝗘𝗔𝗗𝗜𝗡𝗚 & 𝗝𝗔𝗩𝗔 𝟴+ 🔹 synchronized vs volatile 🔹 What is a deadlock? How can you prevent it? 🔹 ExecutorService vs CompletableFuture 🔹 Explain Streams, Lambda Expressions, and Optional. 🔹 What are Virtual Threads in Java 21? 🔥 𝗥𝗢𝗨𝗡𝗗 𝟯 — 𝗦𝗣𝗥𝗜𝗡𝗚 𝗕𝗢𝗢𝗧 & 𝗠𝗜𝗖𝗥𝗢𝗦𝗘𝗥𝗩𝗜𝗖𝗘𝗦 🔹 What is Dependency Injection? 🔹 @Component vs @Service vs @Repository 🔹 How does @Transactional work? 🔹 What is the N+1 query problem in Hibernate/JPA? 🔹 How does JWT authentication work with Spring Security? 🔹 How do microservices communicate with each other? 🔥 𝗥𝗢𝗨𝗡𝗗 𝟰 — 𝗦𝗤𝗟 & 𝗗𝗔𝗧𝗔𝗕𝗔𝗦𝗘𝗦 🔹 INNER JOIN vs LEFT JOIN 🔹 How do indexes improve query performance? 🔹 Explain ACID properties. 🔹 What are transaction isolation levels? 🔹 How would you optimize a slow SQL query? 🔥 𝗥𝗢𝗨𝗡𝗗 𝟱 — 𝗦𝗬𝗦𝗧𝗘𝗠 𝗗𝗘𝗦𝗜𝗚𝗡 & 𝗦𝗖𝗘𝗡𝗔𝗥𝗜𝗢𝗦 🔹 How would you implement Redis caching in Spring Boot? 🔹 Design a rate limiter for a REST API. 🔹 How would you prevent duplicate processing when an API request is retried? 🔹 An API becomes slow in production. How would you debug it? 🔹 How would you implement logging, monitoring, and exception handling in microservices? 🔥 𝗥𝗢𝗨𝗡𝗗 𝟲 — 𝗠𝗔𝗡𝗔𝗚𝗘𝗥𝗜𝗔𝗟 / 𝗛𝗥 🔹 Explain your current project architecture. 🔹 Describe a challenging production issue you resolved. 🔹 Why do you want to join EY? 🔹 Tell me about a technical decision you made and its trade-offs. 🔹 Explain the time and space complexity of your coding solutions.

🚨𝗗𝗜𝗥𝗘𝗖𝗧 𝗧𝗘𝗦𝗧 𝗟𝗜𝗡𝗞 𝗢𝗣𝗣𝗢𝗥𝗧𝗨𝗡𝗜𝗧𝗜𝗘𝗦 🥳🤯 Apply and get Assessment directly 𝗕𝗮𝘁𝗰𝗵 𝗲𝗹𝗶𝗴𝗶𝗯𝗶𝗹𝗶𝘁𝘆: 2020,2021,2022,2023,2024,2025,2026,2027,2028,2029 ✅Multiple Domains Available (jobs/Interships) 💻 Online / WFH Opportunity 📜 Internship Certificate 💼 Boost Your Resume & Skills 💼Salary Up to 10-20 LPA 👉 𝗔𝗽𝗽𝗹𝘆 𝗛𝗲𝗿𝗲: - https://tinyurl.com/j43rf3xf 🔥 𝗔𝗽𝗽𝗹𝘆 𝗡𝗼𝘄 — 𝗟𝗶𝗺𝗶𝘁𝗲𝗱 𝗦𝗹𝗼𝘁𝘀!

TCS Big Data Developer Interview Questions | Technical Round 1 & Managerial Round 2 Sharing some interview questions for candidates preparing for a Big Data Developer role 🔹 Technical Round – Round 1 1. Introduce yourself. 2. Rate your SQL skills on a scale of 1–10. 3. Write a SQL query to find the top 3 employees based on salary from the Employee table. 4. Write a SQL query to find 3 consecutive numbers without any gaps from the Numbers table. 5. Rate your PySpark skills on a scale of 1–10. 6. Write PySpark code to solve Question 4. 7. Explain your project architecture. 8. What optimization techniques have you used in your project? 9. What is the difference between a DataFrame and an RDD? 10. Explain the Catalyst Optimizer and Tungsten Engine. 11. Explain complex data types such as StructType, ArrayType, and MapType. 12. How would you troubleshoot and optimize a Spark job that is experiencing data skew, excessive shuffles, and executor out-of-memory errors? 🔹 Managerial Round – Round 2 1. Introduce yourself. 2. Explain your overall experience in PySpark and SQL. 3. Explain your project architecture. 4. Which environments are you using for development and deployment? 5. Which versions of Spark, Python, and your development platform are you using? 6. Who are your customers, and how are you helping them? 7. Have you completed any certifications in the last three months? 8. Explain SCD Type 2 with sample code. 9. How would you optimize a slow-running Spark job involving data skew, frequent shuffles, and memory issues? 10. How would you design an incremental ETL pipeline to handle late-arriving data, duplicates, and failures?

5 Rounds. 38 LPA. The Goldman Sachs Interview Breakdown Role: Java Backend Developer Application Mode: Direct Application 𝗥𝗼𝘂𝗻𝗱 𝟭: 𝗢𝗻𝗹𝗶𝗻𝗲 𝗔𝘀𝘀𝗲𝘀𝘀𝗺𝗲𝗻𝘁 - Problem 1: Validate a Custom Expression - Given a string with {, }, and *, where * can be {, }, or empty, validate if the expression is balanced. - Problem 2: K Most Frequent Words - Return top-k frequent words sorted by frequency and lexicographical order. 𝗥𝗼𝘂𝗻𝗱 𝟮: 𝗗𝗦𝗔 + 𝗝𝗮𝘃𝗮 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀 - Q1: Reverse Linked List in Pairs, Input: 1 → 2 → 3 → 4 → 5, Output: 2 → 1 → 4 → 3 → 5 - Q2: Core Java Topics - == vs equals() - How HashMap works internally - Collision handling (LinkedList vs Tree in Java 8+) - Load factor reasoning (0.75) - Java Memory Model - Thread safety & concurrency 𝗥𝗼𝘂𝗻𝗱 𝟯: 𝗦𝗽𝗿𝗶𝗻𝗴 𝗕𝗼𝗼𝘁 + 𝗟𝗼𝘄-𝗟𝗲𝘃𝗲𝗹 𝗗𝗲𝘀𝗶𝗴𝗻 - Q1: Rate Limiter Design - Max 5 requests/user/min - Q2: Spring Boot Deep Dive - @Component vs @Service vs @Repository - Bean scopes and lifecycle - Startup process of Spring Boot - Internals of @Transactional and pitfalls 𝗥𝗼𝘂𝗻𝗱 𝟰: 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 + 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻 - Q1: SQL Query Optimization - Indexed WHERE/JOIN fields - Removed SELECT * - Used EXPLAIN - Discussed denormalization & slow log analysis - Q2: API Gateway Auth & Security - OAuth vs JWT - How token expiration works - Can JWTs be invalidated? - Refresh token flows 𝗥𝗼𝘂𝗻𝗱 𝟱: 𝗛𝗥 + 𝗖𝘂𝗹𝘁𝘂𝗿𝗲 𝗙𝗶𝘁 - Why Goldman Sachs? - Handling pressure & deadlines? - Experience with global teams? - Career growth plans?

Wells Fargo is Hiring Technology Program Interns (SDE) i Location: Multiple Eligibility: 2028 Batch Preferred https://www.wellsfargojobs.com/en/jobs/r-557386/2027-technology-program-intern/

IBM IS HIRING INTERNS FOR 2026! 🏢 Company: IBM 💼 Role: Research / Research Software Intern 📂 Tracks: AI & Data, Quantum Algorithms, AI Research 🎓 Qualification: B.E./B.Tech., M.E./M.Tech. or Ph.D. 📊 Academic Criteria: Minimum 70% marks or 7.0 CGPA in the pursuing degree 👨‍💻 Experience: Freshers Apply Here: https://careers.ibm.com/en_US/careers/JobDetail/IBM-Research-Research-Software-Intern/137471

Tiger Analytics Interview Experience Compensation: 21 LPA Position: Data Engineer 1️⃣ How would you design a data pipeline to process millions of financial transactions with high accuracy and low latency? 2️⃣ Explain the differences between OLTP and OLAP systems and their use cases in banking. 3️⃣ Write a SQL query to identify accounts with transactions exceeding a specified threshold within a 24-hour period. 4️⃣ A trade-processing pipeline is producing duplicate records. How would you identify and eliminate the duplicates? 5️⃣ A source system unexpectedly changes a column's datatype, causing pipeline failures. How would you prevent and handle such issues? 6️⃣ Explain the concept of data lineage and why it is important in financial institutions. 7️⃣ A downstream risk reporting application is receiving stale data. How would you investigate the issue? 8️⃣ How would you design a historical data archive strategy while maintaining query performance? 9️⃣ Multiple applications depend on the same dataset, but each requires different refresh frequencies. How would you design the data architecture? 🔟 A critical data load fails just before market opening. What steps would you take to recover quickly and safely? 1️⃣1️⃣ How would you handle late-arriving and out-of-order events in a streaming data pipeline? 1️⃣2️⃣ Write a SQL query to calculate the daily average transaction amount for each customer.

Accenture Interview Experience Role: Senior Software Engineer Here are the exact questions asked across Java, Spring, Hibernate and SQL. 𝗠𝗮𝘃𝗲𝗻 𝗮𝗻𝗱 𝗕𝘂𝗶𝗹𝗱 - What is a Maven build? - What does mvn clean install do? - How do you push code to production? - What is code coverage and line coverage? - How do you improve code coverage when build fails? 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 - How do you verify a method is called twice in Mockito? - In which situations do you use PowerMock? 𝗖𝗼𝗿𝗲 𝗝𝗮𝘃𝗮 - What is the difference between final keyword and final variable? - What is Garbage Collection in Java? - How do you debug and fix OutOfMemoryError? - What are atomic variables in Java? - What is the volatile keyword? - What is the difference between volatile and synchronized? - How do you avoid performance issues caused by synchronization? - What is a BlockingQueue and where do you use it in real applications? - What changes did you make when migrating from Java 7 to Java 8? - What are different ways to ensure thread safety? - What is ThreadLocal and where is it used? 𝗖𝗼𝗹𝗹𝗲𝗰𝘁𝗶𝗼𝗻𝘀 - What is the difference between HashMap and Hashtable? - Why does Hashtable not allow null keys or values? - What is load factor in HashMap? - What does the default load factor 0.75 mean? 𝗦𝗤𝗟 - What is the difference between UNION and UNION ALL? - What is the difference between LEFT JOIN and RIGHT JOIN? - When do you use LEFT JOIN? - How do you find records in one table that have no relationship with another? - How do you handle NULL values and conditional mapping in SQL? - How do you map values like A to Apple, B to Banana in SQL? - How do you remove duplicates in SQL? 𝗛𝗶𝗯𝗲𝗿𝗻𝗮𝘁𝗲 - How do you define relationships between tables in Hibernate? - What are the types of relationships in Hibernate? 𝗦𝗽𝗿𝗶𝗻𝗴 - What is the difference between constructor injection and setter injection? - What happens if you do not use @Autowired in Spring? - How do you perform constructor injection without @Autowired? 𝗗𝗦𝗔 - Find the longest substring without repeating characters in Java? Save this if you are preparing for a Senior Java role.

🚀 EPAM Java Backend Developer Interview Experience | 5+ Years of Experience Recently, I attended an interview for a Senior Java Backend Developer role at EPAM Systems. The discussion covered several important areas of Java backend development, including core concepts, practical coding, Spring Boot, and microservices. Here are some of the key topics worth preparing: 🔹 Core Java • HashMap internals and Collections Framework • Java 8 features, Streams API, and functional interfaces • Multithreading and concurrency • StringBuilder vs StringBuffer 🔹 Spring Boot & Hibernate • Spring Bean lifecycle and auto-configuration • "@Transactional" and transaction propagation • JPA relationships and the N+1 query problem • REST API design and exception handling 🔹 Microservices • Circuit breaker, retry, and fault tolerance • Idempotency and duplicate request handling • Kafka messaging and dead-letter queues • Distributed transactions and the Saga pattern 🔹 Coding & Problem Solving • Longest substring without repeating characters • Grouping anagrams • Finding the first non-repeating character • Java 8 Stream-based coding problems 🔹 SQL & System Design • Query optimization and indexing • Joins and second-highest salary queries • Designing resilient and scalable backend services 💡 My key takeaway: For senior-level interviews, understanding concepts is important, but being able to explain their practical application, trade-offs, and real-world scenarios makes a significant difference.

Infosys L3 Interview Experience 💻 A few months back, before joining my current organization, I went through the Infosys L3 interview process. Sharing my experience for anyone preparing for similar opportunities. Round 1 – Virtual Assessment: Online coding assessment. Round 2 – On-site Coding Round: Similar to the virtual assessment, conducted under supervision at the Infosys center. Round 3 – Technical Interview: A one-on-one interview involving a live coding problem. I had to work through the approach and explain my thought process while solving it. Luckily, the question was quite similar to one Vivek Gupta had covered in his lectures at AlgoZenith, which helped me approach and solve it confidently. The interview focused mostly on scalability, my resume, and system design, alongside the coding problem—important areas to prepare for L3 roles. Final Verdict: Not selected, but the experience was a valuable learning opportunity. Key takeaways: 1) Focus heavily on Dynamic Programming (DP). 2) Go beyond standard DSA sheets and practise tricky variations of familiar problems. 3) Build strong problem-solving skills instead of relying on memorised solutions. 4) Prepare your resume thoroughly and strengthen your system design fundamentals. Hope this helps others preparing for similar interviews!

EY Interview Experience Compensation: 20 LPA Experience: 4+ Years ✅All the Answers of the Below Questions are available in Single Kit - https://lnkd.in/dW_5jZie 1. What happens when you modify a field used in hashCode() after inserting an object into a HashMap? 2. How would you find the second-highest distinct salary for each department using Java Streams? 3. How would you find the second-highest distinct salary for each department using Java Streams? 4. How would you process millions of records without exhausting memory? 5. What happens when a singleton bean injects a prototype-scoped bean? How can you obtain a fresh instance for each operation? 6. How would you choose the right thread-pool size for CPU-bound versus I/O-bound tasks? 7. How do virtual threads differ from platform threads, and what limitations should developers consider? 8. Your microservices have become tightly dependent on each other. How would you identify and prevent a Distributed Monolith? 9. How would you use records, sealed classes, pattern matching, and virtual threads in a modern Java application? 10. How would you troubleshoot a Spring Boot application that starts successfully but fails when a particular endpoint is called? 11. How would you implement OAuth 2.0/JWT security with token expiry, authorization scopes, and service-to-service authentication? 12. How would you design cursor-based pagination for a database containing 100 million records? 13. Payment succeeds, but inventory reservation fails. How would you implement the Saga pattern? 14. How would you prevent cascading failures across 20 microservices? 15. How would you implement distributed tracing and correlation IDs across multiple Spring Boot services? 16. Consumer lag keeps increasing even though all Kafka consumers are running. How would you identify the bottleneck? 17. How would you handle poison messages, retry topics, dead-letter topics, and safe event replay? 18. How would you design a composite database index for filtering transactions by customer and date while supporting sorting? 19. Two concurrent transactions update the same record. Compare optimistic locking with @Version and pessimistic locking. 20. How would you design disaster recovery for a multi-region Java microservices platform? 21. Find the top K frequent elements in a dataset containing billions of records when the data does not fit into memory. 23. Design an API capable of handling 50,000 requests per second. Explain architecture, bottlenecks, and scaling strategy.

Persistent Systems Interview Experience | Position: 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿 | Experience: 𝟯–𝟱 𝘆𝗲𝗮𝗿𝘀 𝗥𝗼𝘂𝗻𝗱 𝟭 - 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 1. Write an SQL query to find employees who earn more than their direct manager. 2. From a transactions table, write a query to identify users who placed more than 20 critical orders every week for at least 1 month. 3. Given a nested JSON file, how would you parse and flatten it in PySpark? 4. How would you design a cost-efficient pipeline in Azure using adf, databricks, and adls? 5. Explain dimensional modeling and how you would design a sales fact table with product and customer dimensions. 𝗥𝗼𝘂𝗻𝗱 𝟮 - 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 1. What is the difference between narrow and wide transformations in Spark? Can you give examples? 2. How would you handle schema evolution in a data lake (e.g., a new column gets added in incoming JSON files)? 3. Explain Slowly Changing Dimensions (SCD Type 2). How would you implement it in Spark? 4. How do you optimize Spark jobs to run faster when dealing with terabytes of data? 5. If you are asked to ingest PDF and image files into your pipeline and make them queryable, how would you design it? 6. Explain the bronze-silver-gold architecture in a data lakehouse. Why is this layering important? 7. Suppose your pipeline needs to run across AWS and Azure together (multi-cloud). How would you design secure and cost-effective data access? 𝗥𝗼𝘂𝗻𝗱 𝟯 - 𝗠𝗮𝗻𝗮𝗴𝗲𝗿𝗶𝗮𝗹 / 𝗕𝗲𝗵𝗮𝘃𝗶𝗼𝗿𝗮𝗹 1. Tell me about a time you handled a production issue under pressure. How did you manage it? 2. How do you explain technical solutions to non-technical clients? 3. Imagine a client has unrealistic expectations on delivery timelines how would you handle it? 4. Describe a situation where you worked with multiple teams having conflicting priorities. How did you manage deadlines?

Walmart Interview Experience | Position: Data Engineer | Experience: 𝟰+ 𝘆𝗲𝗮𝗿𝘀. 𝗥𝗼𝘂𝗻𝗱 𝟭 - 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 1️⃣ How would you design a real-time data pipeline to process millions of financial transactions for fraud detection? 2️⃣ What steps would you take to guarantee data consistency between a production OLTP database and an analytical data warehouse? 3️⃣ You've discovered duplicate records in a critical production dataset. What is your immediate plan to handle them, and what long-term strategy would you implement to prevent recurrence? 4️⃣ A producer team is pushing a schema change that will break your downstream pipeline. How do you manage this schema evolution without causing failure? 5️⃣ How would you systematically debug a Spark job that is running significantly slower in production than in testing? 𝗥𝗼𝘂𝗻𝗱 𝟮 - 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 1️⃣ How do you design a system to secure PII (Personally Identifiable Information) within a data lake while still allowing for authorized analytical access? 2️⃣ Your real-time dashboard is lagging because of Kafka pipeline delays. What’s your troubleshooting methodology? 3️⃣ What is your emergency action plan if a critical data pipeline fails during peak business hours? 4️⃣ How do you strategically manage data partitioning in a petabyte-scale dataset to avoid data skew and optimize query performance? 5️⃣ How would you join two massive datasets that are too large to fit into memory efficiently in a distributed environment? 6️⃣ A daily batch job that normally takes 2 hours is now taking 6 hours. How do you identify the root cause? 𝗥𝗼𝘂𝗻𝗱 𝟯 - 𝗠𝗮𝗻𝗮𝗴𝗲𝗿𝗶𝗮𝗹 / 𝗕𝗲𝗵𝗮𝘃𝗶𝗼𝗿𝗮𝗹 1️⃣ Tell me about a time you handled a production issue under pressure. How did you manage it? 2️⃣ How do you explain technical solutions to non-technical clients? 3️⃣ Imagine a client has unrealistic expectations on delivery timelines — how would you handle it? 4️⃣ Describe a situation where you worked with multiple teams having conflicting priorities. How did you manage deadlines?

🚀 #AMDOCS Round 1 Interview Questions Senior Test Automation role requiring 11+ years of Python, Pytest, Selenium & AI 1. Reverse each word without changing word order: "python automation using selenium". 2. Check whether a number is prime. 3. Find a number’s index efficiently in an unsorted list. 4. Find the key with the maximum value in a dictionary. 5. Reverse any two words in a three-word sentence. 6. What are the fixture scopes in Pytest? 7. How does yield work in a fixture? 8. How do you mark tests in Pytest? 9. Write an XPath to locate a BookMyShow link using its text. 10. How do you generate an HTML report for Selenium tests? 11. Write a query to combine two tables using a JOIN. 12. What is the difference between path and query parameters? 13. How can AI help generate test cases? 14. How do you validate AI-generated automation code?

Uber Interview Experience | Position: Data Engineer 𝗥𝗼𝘂𝗻𝗱 𝟭 — 𝗦𝗤𝗟 / 𝗣𝗿𝗼𝗯𝗹𝗲𝗺 𝗦𝗼𝗹𝘃𝗶𝗻𝗴 1️⃣ Write an SQL query to find the top 3 drivers by average rating, only including drivers with more than 100 trips. 2️⃣ Find users who booked a ride more than once within a 10-minute window (use self-join or window functions). 3️⃣ Given a rides table, find the most frequently traveled route in the past 30 days. 4️⃣ Write an efficient query to detect duplicates based on customer ID and timestamp but only return the latest record. 5️⃣ Find the difference in trip counts between two consecutive weeks for each driver. 𝗥𝗼𝘂𝗻𝗱 𝟮 — 𝗗𝗦𝗔 / 𝗔𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺 1️⃣ Given a stream of integers, design a data structure to return the median at any time. 2️⃣ Detect a cycle in a directed graph representing trip routes between cities. 3️⃣ Merge K sorted linked lists. 4️⃣ Implement an LRU (Least Recently Used) cache. 5️⃣ Given a list of ride timestamps, find the longest continuous ride streak. 𝗥𝗼𝘂𝗻𝗱 𝟯 — 𝗦𝘆𝘀𝘁𝗲𝗺 𝗗𝗲𝘀𝗶𝗴𝗻 / 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 1️⃣ Design a distributed pipeline to detect ride anomalies in real time using stream processing. 2️⃣ How would you scale a pipeline that ingests 100M GPS events per day and still serves analytics queries under 1 second? 3️⃣ Design a versioned schema system for your data warehouse to handle backward-incompatible changes. 4️⃣ How would you implement exactly-once delivery in a Kafka + Spark Structured Streaming setup? 5️⃣ Explain how you handle late-arriving data in real-time processing (with watermarks and state cleanup).

In my 2nd year at DTU, I solved 700+ LeetCode problems and still had no idea which ones were most important for Google and other product companies. Today, someone has put company-wise questions on GitHub for free. If you're preparing for coding interviews, these 10 repos will save you months: 1. LeetCode Company-wise Problems (the repo in this tweet) ⭐ 31.7k Questions grouped by company, with separate lists for the last 30, 60 and 90 days. https://lnkd.in/dt4YXVVY 2. Hello Algo ⭐ 131k A free DSA book with animations for every concept, in English and 10+ languages of code. https://lnkd.in/dvJNV_tR 3. Algorithm Visualizer ⭐ 48.9k Watch your code run step by step. Recursion and graphs finally make sense. https://lnkd.in/dTa27FZ9 4. Coding Patterns for DSA Interviews ⭐ 4.9k Sliding window, two pointers, fast & slow pointers and more, with problems for each. https://lnkd.in/dmMgvHbW 5. The Algorithms (Java) ⭐ 66.4k Every major algorithm written in clean Java. There's a C++ and Python version too. https://lnkd.in/dR6PUCkT 6. LeetCode Solutions ⭐ 6k Python and C++ solutions for all 4,000+ LeetCode problems, updated every week. https://lnkd.in/dywRmY7C 7. William Fiset's Algorithms ⭐ 18.8k Clean implementations, many with companion videos on his YouTube channel. His graph theory series is one of the best out there. https://lnkd.in/d5CbRgsh 8. CP Algorithms ⭐ 11.3k Graphs, number theory and strings explained properly. For when the editorial isn't enough. https://lnkd.in/duRbS9RT 9. Awesome Competitive Programming ⭐ 14.2k Everything you need if you want to start giving weekly contests. https://lnkd.in/dQzwKYna 10. Interviews ⭐ 65.3k DSA, core CS and practice links for the full interview, in one place. https://lnkd.in/dN2FY_hB

🚀 Accenture .NET Developer Interview Experience | 5 YOE Recently, I appeared for a technical interview for a Full-Stack .NET Developer role. I'm sharing important questions based on my interview experience to help fellow developers prepare for Accenture interviews. 💻 C# & .NET Value types vs. reference types? How do async and await work? Task vs. Thread vs. Task.Run()? Delegates vs. events? IEnumerable vs. IQueryable? How does Garbage Collection work? Explain SOLID principles. Transient vs. Scoped vs. Singleton? 🌐 ASP.NET Core Web API 9. Explain the middleware pipeline. 10. Authentication vs. authorization? How does JWT work? 11. How do you handle global exceptions? 12. Middleware vs. filters? 13. How do you implement API versioning and validation? 14. How do you secure REST APIs? 15. In-memory caching vs. Redis? 16. How do you troubleshoot a slow API? 🏗️ EF Core & Architecture 17. EF Core vs. Dapper? 18. Eager vs. lazy vs. explicit loading? 19. What is the N+1 query problem? 20. Explain the Repository Pattern. 21. What is CQRS? 22. Explain Clean Architecture. 🅰️ Angular & TypeScript 23. Explain OnPush change detection. 24. Promises vs. Observables? 25. switchMap vs. mergeMap vs. concatMap vs. exhaustMap? 26. Explain interceptors and route guards. 27. How do you optimize Angular performance? 28. Reactive forms vs. template-driven forms? 29. How do you manage shared state? 30. How do you prevent memory leaks? 🗄️ SQL Server 31. Clustered vs. non-clustered indexes? 32. Find the Nth-highest salary using SQL. 33. How do you analyze execution plans? 34. What causes deadlocks, and how do you resolve them? 35. Explain transactions and isolation levels. ⚙️ System Design & Real-World Scenarios 36. How would you design a scalable .NET + Angular application? 37. How would you prevent duplicate invoice generation under concurrent requests? 38. How would you optimize pagination for millions of records? 39. Describe a production issue you solved and how you identified its root cause. 🎯 For developers with around 5 years of experience, focus on practical implementation, performance optimization, architecture, security, and real-world troubleshooting—not just theoretical definitions.

PayPal Interview Experience | Compensation Range: 29LPA + 2.9L variable |Position: Data Engineer | Application Method: via referral 𝗥𝗼𝘂𝗻𝗱 𝟭: 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 – 𝗗𝗦𝗔 + 𝗦𝗤𝗟 (𝟰𝟱 𝗺𝗶𝗻𝘀) Data Structures & Algorithms: • Rainwater Trapping – optimized for space and time • Priority Queue-based problem for task scheduling • Array traversal using prefix sums and sliding window patterns SQL: • Extensive use of window functions – ROW_NUMBER, RANK, LAG, LEAD • Aggregations, partitions, and advanced joins • Query optimization and performance tuning techniques 𝗥𝗼𝘂𝗻𝗱 𝟮: 𝗧𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗗𝗲𝘀𝗶𝗴𝗻 + 𝗣𝘆𝗦𝗽𝗮𝗿𝗸 (𝟰𝟱–𝟲𝟬 𝗺𝗶𝗻𝘀) Project-Based Discussion: • Shared architecture of prior data pipelines • Justified choices of tools like Airflow, Glue, Kafka, Snowflake • Discussed strategies for data validation, monitoring, and scalability System Design Scenario: • Data migration from Hadoop, Oracle DB, and S3 → unified S3 data lake • Focused on scalability, error handling, schema management, and fault tolerance Spark Coding Task: • DataFrame joins and transformations in PySpark • Handled edge cases like null values, schema mismatches, and skewed data • Output written in partitioned Parquet format 𝗥𝗼𝘂𝗻𝗱 𝟯: 𝗠𝗮𝗻𝗮𝗴𝗲𝗿𝗶𝗮𝗹 + 𝗦𝗰𝗲𝗻𝗮𝗿𝗶𝗼-𝗕𝗮𝘀𝗲𝗱 (𝟲𝟬 𝗺𝗶𝗻𝘀) • In-depth discussion on project ownership and collaboration with cross-functional teams • Real-time problem scenarios like pipeline delays, replication lags, and Spark job failures • Behavioral focus: adaptability, leadership under pressure, and communication 𝗥𝗼𝘂𝗻𝗱 𝟰: 𝗛𝗥 𝗗𝗶𝘀𝗰𝘂𝘀𝘀𝗶𝗼𝗻 • Offer structure, benefits, and company policies • Discussion on organizational values and career progression opportunities • Cultural alignment and long-term vision Key Takeaways: • The interview process was balanced across technical, design, and behavioral areas • Strong emphasis on SQL, PySpark, and scalable data pipeline design • Communication, clarity in thought, and structured problem-solving played a key role

*FREE Claude AI Masterclass- From Prompting to Building* 🤳🏼⚙️💻 Build AI Agents for Real-World Applications in 120 Minutes. 💯 🔖No prior AI experience needed Eligibility :- Freshers • Working Professionals 📅 Date: 24 October 2026 ⏰ 7:00 PM 💻 Mode:Online 🔗 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗙𝗼𝗿 𝗙𝗥𝗘𝗘👇 : https://rebrand.ly/claudefreemasterclass 📢 Share this opportunity with your friends.

I cracked Microsoft in my first attempt! 🚀✌️ Here are 11 DSA problems I repeatedly practised before the interviews: 𝟏. 𝐓𝐰𝐨 𝐒𝐮𝐦: Hashing, Arrays 𝟐. 𝐌𝐞𝐫𝐠𝐞 𝐈𝐧𝐭𝐞𝐫𝐯𝐚𝐥𝐬: Sorting, Greedy 𝟑. 𝐅𝐢𝐧𝐝 𝐅𝐢𝐫𝐬𝐭 𝐚𝐧𝐝 𝐋𝐚𝐬𝐭 𝐏𝐨𝐬𝐢𝐭𝐢𝐨𝐧 𝐨𝐟 𝐄𝐥𝐞𝐦𝐞𝐧𝐭: Binary Search 𝟒. 𝐃𝐞𝐭𝐞𝐜𝐭 𝐂𝐲𝐜𝐥𝐞 𝐢𝐧 𝐚 𝐋𝐢𝐧𝐤𝐞𝐝 𝐋𝐢𝐬𝐭: Linked List, Floyd’s Cycle Detection 𝟓. 𝐋𝐑𝐔 𝐂𝐚𝐜𝐡𝐞: HashMap + Doubly Linked List (Design, O(1) Operations) 𝟔. 𝐒𝐮𝐛𝐬𝐞𝐭𝐬: Recursion, Backtracking 𝟕. 𝐊𝐭𝐡 𝐋𝐚𝐫𝐠𝐞𝐬𝐭 𝐄𝐥𝐞𝐦𝐞𝐧𝐭 𝐢𝐧 𝐚𝐧å 𝐀𝐫𝐫𝐚𝐲: Heap (Priority Queue) 𝟖. 𝐋𝐨𝐧𝐠𝐞𝐬𝐭 𝐏𝐚𝐥𝐢𝐧𝐝𝐫𝐨𝐦𝐢𝐜 𝐒𝐮𝐛𝐬𝐭𝐫𝐢𝐧𝐠: Dynamic Programming (DP), Strings 𝟗. 𝐖𝐨𝐫𝐝 𝐁𝐫𝐞𝐚𝐤: Dynamic Programming, Trie (Optional) 𝟏𝟎. 𝐃𝐢𝐣𝐤𝐬𝐭𝐫𝐚’𝐬 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦: Graphs, Shortest Path, Priority Queue 𝟏𝟏. 𝐇𝐚𝐦𝐢𝐥𝐭𝐨𝐧𝐢𝐚𝐧 𝐏𝐚𝐭𝐡: Graphs, Backtracking, Bitmask DP (Advanced)