PubMatic Data Analyst Interview Questions + Guide in 2025

PubMatic is an independent technology company that maximizes customer value by delivering innovative solutions in the digital advertising supply chain.

As a Data Analyst at PubMatic, you will play a crucial role in the Finance Reporting & Insights function, where you will be responsible for collecting, analyzing, and interpreting large datasets to provide actionable insights for finance and operations teams. Key responsibilities include leveraging tools such as SQL, Microsoft Excel, and BI visualization tools to create comprehensive dashboards and reports that highlight primary metrics essential for decision-making. A strong analytical mindset, attention to detail, and the ability to communicate complex data in an understandable manner are essential traits for success in this role. Additionally, familiarity with data processing technologies and programming languages, including Python, will enhance your effectiveness in extracting valuable information from diverse data sources.

This guide will equip you with the necessary knowledge and insights to excel in your interview for the Data Analyst position at PubMatic, helping you demonstrate your analytical abilities and align with the company's values.

The interview process for a Data Analyst position at PubMatic is structured to assess both technical skills and cultural fit within the organization. It typically consists of three main rounds, each designed to evaluate different aspects of your capabilities.

1. Initial Screening

The first step in the interview process is an initial screening, which usually takes place over a 30-minute phone call with a recruiter. During this conversation, the recruiter will discuss your background, experience, and motivation for applying to PubMatic. They will also provide insights into the company culture and the specifics of the Data Analyst role. This is an opportunity for you to showcase your communication skills and express your interest in the position.

2. Technical Interviews

Following the initial screening, candidates typically undergo two technical interviews. These interviews are conducted online and focus heavily on your proficiency in SQL and Python, as well as your analytical skills. You can expect to answer questions related to data manipulation, querying databases, and solving problems using programming. Interviewers may present you with real-world scenarios or datasets to analyze, requiring you to demonstrate your ability to extract meaningful insights and present them clearly.

3. Final Interview

The final round is often a more in-depth technical interview that may include a case study or a practical assessment. In this round, you might be asked to create reports or dashboards using BI tools, showcasing your ability to visualize data effectively. Additionally, behavioral questions may be included to assess your problem-solving approach and how you work within a team. This round is crucial for determining how well you align with PubMatic's values and how you can contribute to the Finance Reporting & Insights function.

As you prepare for these interviews, it's essential to familiarize yourself with the types of questions that may be asked, particularly those that focus on your technical skills and past experiences.

Here are some tips to help you excel in your interview.

Understand the Role and Its Impact

Before your interview, take the time to deeply understand the responsibilities of a Data Analyst at PubMatic. Familiarize yourself with how the role contributes to the Finance Reporting & Insights function and how it supports the overall business objectives. Be prepared to discuss how your analytical skills can help extract valuable insights from data, ultimately aiding the finance and operations teams in making informed decisions.

Master SQL and Python Fundamentals

Given the emphasis on SQL and Python in the role, ensure you have a solid grasp of both. Brush up on SQL queries, especially those involving data retrieval, table creation, and complex joins. Practice writing Python scripts that can manipulate data, as you may be asked to solve problems or demonstrate your coding skills during the interview. Being able to articulate your thought process while solving these problems will showcase your analytical mindset.

Prepare for Technical Questions

Expect the interview to include technical questions that assess your knowledge of data analysis tools and techniques. Be ready to discuss your experience with Excel, including advanced functions like pivot tables and macros. Familiarize yourself with BI tools and how you can leverage them to create dashboards and visualizations. Demonstrating your ability to present data in an easy-to-understand format will be crucial.

Showcase Your Problem-Solving Skills

During the interview, you may be presented with real-world scenarios or case studies. Approach these problems methodically, breaking them down into manageable parts. Highlight your logical reasoning and analytical skills as you work through the problem. This will not only demonstrate your technical abilities but also your capacity to think critically under pressure.

Communicate Effectively

Given the collaborative nature of the role, strong communication skills are essential. Practice articulating your thoughts clearly and concisely. Be prepared to discuss your previous experiences and how they relate to the role at PubMatic. Tailor your responses to reflect how your background aligns with the company’s values and the specific needs of the team.

Embrace the Company Culture

PubMatic values diversity and inclusion, so be sure to reflect this in your interactions. Show enthusiasm for the company’s mission and culture, and be prepared to discuss how you can contribute to a positive team environment. Understanding the hybrid work model and expressing your adaptability to both in-office and remote work will also resonate well with the interviewers.

Follow Up Thoughtfully

After the interview, consider sending a thank-you note that reiterates your interest in the position and reflects on specific points discussed during the interview. This not only shows your appreciation for their time but also reinforces your enthusiasm for the role and the company.

By following these tips, you’ll be well-prepared to make a strong impression during your interview at PubMatic. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Analyst interview at PubMatic. The interview process will likely focus on your technical skills, particularly in SQL and Python, as well as your analytical abilities and experience with data visualization tools. Be prepared to discuss your previous work experience and how it relates to the responsibilities outlined in the job description.

SQL and Database Management

1. Can you explain the difference between INNER JOIN and LEFT JOIN in SQL?

Understanding joins is crucial for data manipulation and retrieval.

How to Answer

Explain the basic definitions of INNER JOIN and LEFT JOIN, and provide a scenario where each would be used.

Example

"An INNER JOIN returns only the rows that have matching values in both tables, while a LEFT JOIN returns all rows from the left table and the matched rows from the right table. For instance, if I have a table of customers and a table of orders, an INNER JOIN would show only customers who have placed orders, whereas a LEFT JOIN would show all customers, including those who haven't placed any orders."

2. How would you write a SQL query to find the third highest salary from a table?

This question tests your ability to write complex SQL queries.

How to Answer

Discuss the use of subqueries or the DISTINCT keyword to achieve the desired result.

Example

"I would use a subquery to first select distinct salaries and then use the LIMIT clause to get the third highest. The query would look something like this: SELECT DISTINCT salary FROM employees ORDER BY salary DESC LIMIT 1 OFFSET 2;"

3. Describe how you would create a table in SQL.

This question assesses your understanding of SQL syntax and database design.

How to Answer

Outline the basic structure of a CREATE TABLE statement, including data types.

Example

"To create a table, I would use the CREATE TABLE statement followed by the table name and the column definitions. For example: CREATE TABLE employees (id INT PRIMARY KEY, name VARCHAR(100), salary DECIMAL(10, 2)); This defines a table with three columns: id, name, and salary."

4. What are some common SQL functions you have used?

This question evaluates your practical experience with SQL.

How to Answer

Mention functions like COUNT(), SUM(), AVG(), and how you have applied them in your work.

Example

"I frequently use functions like COUNT() to determine the number of records that meet certain criteria, SUM() to calculate total sales, and AVG() to find average values. For instance, I used SUM() to analyze total revenue generated from different ad campaigns."

5. How do you optimize a SQL query?

This question tests your knowledge of performance tuning.

How to Answer

Discuss indexing, query structure, and avoiding unnecessary columns in SELECT statements.

Example

"I optimize SQL queries by ensuring that I use indexes on columns that are frequently searched or joined. Additionally, I avoid using SELECT * and instead specify only the columns I need, which reduces the amount of data processed."

Python and Data Analysis

1. How would you find the odd number from a given list in Python?

This question assesses your basic programming skills in Python.

How to Answer

Explain the logic you would use to iterate through the list and identify odd numbers.

Example

"I would use a simple loop to iterate through the list and check if each number is odd using the modulus operator. For example: for num in my_list: if num % 2 != 0: print(num)."

2. Can you explain how you would use Python for data visualization?

This question evaluates your experience with data visualization libraries.

How to Answer

Mention libraries like Matplotlib or Seaborn and how you have used them to create visualizations.

Example

"I often use Matplotlib and Seaborn for data visualization. For instance, I created a bar chart to visualize the revenue generated by different ad formats using Matplotlib's plt.bar() function, which helped the team quickly identify the most profitable formats."

3. What libraries in Python are you familiar with for data analysis?

This question assesses your familiarity with Python libraries.

How to Answer

List libraries such as Pandas, NumPy, and any others you have used.

Example

"I am familiar with Pandas for data manipulation and analysis, NumPy for numerical operations, and Matplotlib for data visualization. I often use Pandas to clean and prepare data before analysis."

4. How do you handle missing data in a dataset using Python?

This question tests your data cleaning skills.

How to Answer

Discuss methods like imputation, dropping missing values, or using libraries to handle missing data.

Example

"I handle missing data by first assessing the extent of the missing values. Depending on the situation, I might use imputation methods to fill in missing values or drop rows/columns with excessive missing data using Pandas' dropna() function."

5. Describe a project where you used Python to analyze data.

This question allows you to showcase your practical experience.

How to Answer

Provide a brief overview of the project, the data you analyzed, and the insights you gained.

Example

"In a recent project, I analyzed user engagement data from our ad campaigns using Python. I utilized Pandas to clean the data and Matplotlib to visualize trends over time. The analysis revealed that certain ad formats had significantly higher engagement rates, which informed our future marketing strategies."