Solving a REAL JP Morgan SQL Interview Questions

🧠 Don’t miss out! Get FREE access to my Skool community — packed with resources, tools, and support to help you with Data, Machine Learning, and AI Automations! 📈 https://www.skool.com/data-and-ai-automations-4579 Today we are taking a look at a JP Morgan SQL interview questions for Data Analysts/Scientists. Both of these examples come directly from DataLemur. Everything is coded within MSSQL and inside SQL Server Management Studio. SQL Interview Question here: https://datalemur.com?referralCode=e6YqaKye 🚀 Hire me for Data Work: https://ryanandmattdatascience.com/data-freelancing/ 👨‍💻 Mentorships: https://ryanandmattdatascience.com/mentorship/ 📧 Email: [email protected] 🌐 Website & Blog: https://ryanandmattdatascience.com/ 🖥️ Discord: https://discord.com/invite/F7dxbvHUhg 📚 *Practice SQL & Python Interview Questions: https://stratascratch.com/?via=ryan 📖 *SQL and Python Courses: https://datacamp.pxf.io/XYD7Qg 🍿 WATCH NEXT Real SQL Interview Questions Playlist: https://www.youtube.com/playlist?list=PLcQVY5V2UY4LvbRTDRVmcqZPkhCqk4Ax9 Robinhood SQL Interview Question: https://youtu.be/hM2-vq8Ygi4 TikTok SQL Interview Question: https://youtu.be/aV3OVBkNXfA CVS SQL Interview Question: https://youtu.be/Yio3dE-WdzU Looking to land a data analyst role at JPMorgan or another top bank? In this video, I walk through a medium-difficulty SQL interview question that tests your ability to analyze credit card launch data. This is the kind of real-world problem you'll encounter during technical interviews at major financial institutions. The challenge asks you to estimate how many cards will be issued in the first month of a new credit card launch by analyzing historical launch data. I break down the problem step by step, showing you how to identify the launch month (the earliest record in the monthly cards issued table), use window functions with PARTITION BY to rank cards by their issue dates, and handle edge cases like year transitions. We'll write a complete SQL query using CTEs (Common Table Expressions), the RANK() window function, and proper ordering to output the credit card name and the number of cards issued during launch month, sorted from highest to lowest issuance. I explain my thought process throughout, including why I order by both issue year and month to avoid ranking errors, and how to structure clean, readable SQL code that impresses interviewers. By the end of this walkthrough, you'll understand how to approach partition-based ranking problems and apply these SQL skills to real data analyst interview questions. If you're preparing for interviews at JPMorgan, Goldman Sachs, Morgan Stanley, or any financial services company, this tutorial will help you master essential SQL concepts. TIMESTAMPS 00:00 Introduction & Problem Overview 00:49 Understanding the Requirements 01:42 Starting the Query Solution 02:38 Testing the Initial Code 03:05 Building the WITH Statement 04:01 Final Query & Submission 04:34 Solution Explanation OTHER SOCIALS: Ryan’s LinkedIn: https://www.linkedin.com/in/ryan-p-nolan/ Matt’s LinkedIn: https://www.linkedin.com/in/matt-payne-ceo/ Twitter/X: https://x.com/RyanMattDS Who is Ryan Ryan is a Data Scientist at a fintech company, where he focuses on fraud prevention in underwriting and risk. Before that, he worked as a Data Analyst at a tax software company. He holds a degree in Electrical Engineering from UCF. Who is Matt Matt is the founder of Width.ai, an AI and Machine Learning agency. Before starting his own company, he was a Machine Learning Engineer at Capital One. *This is an affiliate program. We receive a small portion of the final sale at no extra cost to you.