Nick’s previously held Software & Data roles at Facebook, Google, & SafeGraph (a geospatial analytics startup).
Currently, he’s the best-selling author of Ace the Data Science Interview, and Founder & CEO of DataLemur.
Nick’s also active on LinkedIn, where he shares career tips with his 160,000+ followers.
When it comes to the integrated circuit design industry, Cadence Design Systems uses SQL to manage customer information and look at huge amounts of data about semiconductor designs. This is why Cadence Design Systems LOVES to ask SQL query questions during job interviews for Data Science, Data Engineering, and Data Analytics.
If you’re trying to get ready for the SQL Assessment, here are 10 practice questions from recent interviews at Cadence Design Systems that are similar to the ones you might be asked. See how many you can answer correctly?
Interviewing at Cadence Design Systems can be an exciting yet nerve-wracking experience. As a leading company in electronic design automation software and engineering services, Cadence interviews are known to be quite rigorous.
Coming prepared with strong answers to the most commonly asked behavioral and technical questions is key to standing out amongst the competition. In this article, we’ll breakdown the types of Cadence interview questions you’re likely to encounter and provide tips on how to craft winning responses.
Overview of the Cadence Interview Process
The Cadence interview process typically consists of at least two rounds:
-
Phone/Video Screen – 30-45 minute preliminary interview focused on behavioral questions and a high-level assessment of technical skills.
-
On-site Interview – 4-8 hour on-site interview including a mix of technical questions, coding challenges, behavioral questions, and multiple interviews with engineers, managers, and executives.
The on-site interview is comprehensive and rigorous. You can expect questions on data structures, algorithms, operating systems, programming languages, databases, Cadence tools/technology, system design, troubleshooting, and debugging.
Preparation is key as the bar is high. Cadence wants to ensure you have the hard skills and critical thinking ability to perform in a complex, fast-paced engineering environment. In addition to technical ability, they also assess cultural fit.
Common Cadence Behavioral Interview Questions and Answers
Behavioral questions allow interviewers to understand your thought process, values, and how you might engage with coworkers. Some common behavioral questions at Cadence include:
Q: Tell me about yourself.
A: Focus on your technical background and skills relevant to the role. Provide 2-3 specific examples of relevant projects or experiences. Conclude with your interest in Cadence and the position.
Q: Why do you want to work at Cadence?
A: Show passion for their tools, technology, and mission. Explain why Cadence aligns with your career goals and interests. Reference specifics on their innovation, values, and culture. Conclude with why you’re a great fit.
Q: How do you respond to high-pressure situations or tight deadlines?
A: Share a relevant example. Explain your approach to time management, focusing energy, and delivering under pressure. Emphasize remaining calm, collaborating with your team, and effectively prioritizing tasks.
Q: Tell me about a time you faced a conflict at work. How did you handle it?
A: Choose an appropriate conflict scenario. Explain the conflicting viewpoints and how you actively listened to understand all perspectives. Share how you found common ground and came to a resolution or compromise. Emphasize teamwork, empathy, and communication.
Q: What do you consider your greatest weakness?
A: Choose a minor weakness unrelated to the role. Explain how you’ve taken proactive steps to improve in this area. Pivot to a positive by sharing a related strength.
Technical Cadence Interview Questions and Answers
Cadence technical interviews will assess your knowledge across a range of core engineering disciplines. Brush up on the following high-probability question areas:
Programming Languages and Object-Oriented Design
-
Explain core OOP concepts like inheritance, encapsulation, abstraction, and polymorphism. Understand how to implement them syntactically in languages like C++, Java, Python.
-
Be ready to design classes, interfaces, and methods for real-world objects and scenarios. Explain your choice of fields, relationships, and key behaviors.
-
Know common design patterns like singleton, factory, observer, strategy, and when to use them.
-
Review core language fundamentals and syntax for C++, Java, Python, Perl, TCL.
Data Structures and Algorithms
-
Explain when and why to use arrays vs linked lists vs hash tables vs trees vs graphs. Know the time and space complexity tradeoffs.
-
Implement common algorithms like binary search, merge sort, quick sort recursively. Explain the complexity analysis.
-
Traverse trees, graphs, and strings recursively. Reverse a linked list iteratively and recursively.
-
Identify when to apply algorithms like BFS vs DFS, Dijkstra’s, A*, KMP string matching.
Databases and SQL
-
Know concepts like ACID transactions, normalization, indexing, schemas, CRUD operations.
-
Write basic SELECT queries including JOINs, aggregates, subqueries, grouping. Normalize data to 3NF.
-
Explain tradeoffs between relational SQL databases like MySQL vs NoSQL databases like MongoDB.
Operating Systems and Threading
-
Explain processes vs threads. Know how context switching, race conditions, and locking work.
-
Understand deadlock, livelock, starvation. Know how to avoid.
-
Implement producer-consumer and reader-writer problems with semaphores and mutexes.
-
Know memory management techniques like paging, segmentation, virtual memory.
Software Engineering and System Design
-
Consider scale, performance, security, availability when designing large systems. Know leading practices.
-
Explain how you approach requirements gathering, system modeling, UML, testing, QA, deployment, maintenance.
-
Review networking concepts like OSI model, TCP/IP, HTTP, DNS, load balancing, caching strategies.
-
Identify metrics to measure, monitor and optimize system performance. Know design patterns like microservices.
Mastering the Cadence Coding Interview
Many of the Cadence engineering roles involve some level of coding interviews. Here are some tips to ace the coding portion:
-
Clarify the problem completely before diving into coding. Ask thoughtful questions.
-
Think through the inputs, outputs, edge cases, sample test data.
-
Explain your high-level approach before writing code.
-
Write clean, well-commented, well-formatted code with good variable names.
-
Consider time and space complexity. Strive to be optimal.
-
Test your code thoroughly with provided test data. Walk through examples.
-
Communicate constantly. Verbalize your thought process as you code.
-
Ask for feedback on your code. Improve it if time allows.
Preparing responses and practicing for the coding interview questions ahead of time will help ensure a smooth process.
With its challenging behavioral and technical multi-round interview process, Cadence sets a high bar for its software engineering roles.
Come armed with confidence by spending time targeting your preparation to the exact areas outlined above. Understand Cadence’s tools and technology. Refresh key computer science and programming fundamentals. Practice communicating your approach clearly and coding efficiently.
With diligent preparation, you’ll be ready to impress your Cadence interviewers and highlight why you’re the ideal engineering candidate to join their innovative team. Best of luck on your upcoming Cadence interview!
SQL Question 8: Analyzing Ad Click-Through Rates
You have been asked to look at the click-through rates (CTR) of different digital ads that Cadence Design Systems is running as a data analyst. Cadence makes and sells software and hardware for electronic design automation (EDA). They also run a series of ads to get people to download trial versions of their products. The person in charge of you wants to know how many people click on the ad and then start a software trial.
Please find the click-through rate, which is the number of trials a user started divided by the number of times that user saw the ad, all multiplied by 100. Provide results table for all users.
Now, lets say we have two tables: and .
| view_id | user_id | ad_id | view_date |
|---|---|---|---|
| 101 | 1001 | 201 | 2022-10-10 |
| 102 | 1002 | 202 | 2022-10-11 |
| 103 | 1001 | 201 | 2022-10-12 |
| 104 | 1003 | 203 | 2022-10-13 |
| 105 | 1001 | 201 | 2022-10-14 |
| trial_id | user_id | product_id | start_date |
|---|---|---|---|
| 901 | 1001 | 301 | 2022-10-12 |
| 902 | 1003 | 302 | 2022-10-14 |
| 903 | 1001 | 301 | 2022-10-15 |
| 904 | 1002 | 303 | 2022-10-16 |
| 905 | 1001 | 301 | 2022-10-18 |
| user_id | ctr |
|---|---|
| 1001 | 66.67 |
| 1002 | 50.00 |
| 1003 | 100.00 |
This query first joins the and tables on the . Then it keeps track of how many unique s and s there are for each user, figures out the ratio of trials to views, and multiplies that number by 100 to get a percentage. Finally, it returns this click-through rate for each user.
Check out this SQL interview question from TikTok on DataLemurs, where you can practice solving a similar rate-based problem:
SQL Question 6: Average usage hours of software product per client
Given a database with usage logs of Cadence’s software products by their clients, find the average number of hours each client used each software product during the given time period.
| log_id | client_id | product_id | usage_date | hours_used |
|---|---|---|---|---|
| 1 | 100 | 561 | 01/08/2022 | 5 |
| 2 | 200 | 561 | 01/09/2022 | 8 |
| 3 | 100 | 561 | 02/08/2022 | 7 |
| 4 | 200 | 741 | 01/10/2022 | 6 |
| 5 | 100 | 741 | 01/11/2022 | 4 |
The above query sorts the data by both client_id and product_id, then uses the AVG function on the hours_used column to get an idea of how much each client usually uses an item. It is important to note that usage logs for each product by each client over the whole period are being looked at. You can add an extra WHERE clause to filter dates based on the need if the time period needs to be narrowed down.
| client_id | product_id | avg_usage |
|---|---|---|
| 100 | 561 | 6 |
| 200 | 561 | 8 |
| 200 | 741 | 6 |
| 100 | 741 | 4 |
To practice another question about calculating rates, try this TikTok SQL question on DataLemurs interactive coding environment:
