Round 1: Technical 

✅ DSA Questions:

🔹 Rainwater Trapping Problem: A classic algorithmic challenge focused on optimizing space and time complexity.

🔹 Priority Queue Problem: Related to task prioritization, though I don’t recall the exact details.

✅ SQL Questions:

🔹 Focused on window functions, their applications, and strategies to optimize SQL queries.

Round 2: Technical (Design Round)

✅ Project Discussion:

🔹 Shared insights into my previous projects.

🔹 Discussed best practices in software and data engineering, explaining how I implemented them in real-world scenarios.

✅ Design Question:

🔹 Scenario: Design a solution to migrate data from multiple sources (Hadoop, S3, and Oracle DB) to a final S3 bucket.

🔹 Focus: Explained service and tool selection, with emphasis on: Error logging, Scalability, Fault tolerance

✅ Spark Coding Challenge:

🔹 Task: Given two data frames, perform data processing and store the final output in another data frame.

🔹 Skills Evaluated: Proficiency in PySpark and data transformation logic.

Round 3: Managerial

✅ Projects Discussion:

🔹 A detailed discussion on my projects, focusing on: The rationale behind choosing specific tools and services.

🔹 Challenges faced and how I overcame them.

✅ Real-Life Scenario Questions:

Examples of handling pipeline issues, such as: 

🔹 Managing overload situations.

🔹 Resolving service downtimes.

✅ Behavioral Questions:

🔹 Emphasized problem-solving, teamwork, and adaptability skills through situational examples.

Round 4: HR 

🔹 Discussion of offer details and PayPal’s compensation structure.

🔹 Standard behavioral questions related to:

🔹 Company culture.

🔹 Alignment with PayPal’s values and expectations.

✅ Key Takeaways

🔹 The interview process was thorough, testing a mix of technical, design, and interpersonal skills.

🔹 Each round had a clear purpose and evaluation criteria, ensuring a holistic assessment.

🔹 It was an excellent opportunity to showcase both technical proficiency and problem-solving abilities.