Looker Data Scientist Interview Questions + Guide in 2025

Looker is a powerful data exploration and business intelligence platform that helps organizations make data-driven decisions.

A Data Scientist at Looker plays a crucial role in analyzing complex datasets to derive actionable insights that drive business growth. Key responsibilities include utilizing SQL for data manipulation, developing data models, and collaborating with cross-functional teams to implement data-driven strategies. A successful candidate will possess strong analytical skills, proficiency in SQL, and a solid understanding of business intelligence concepts. Looker values teamwork, innovation, and a customer-centric approach, making it essential for candidates to also exhibit strong communication skills and a proactive mindset. This guide will prepare you to navigate the interview process effectively, ensuring you’re well-equipped to showcase your skills and align with Looker’s values.

The interview process for a Data Scientist role at Looker is structured to assess both technical skills and cultural fit within the team. The process typically unfolds as follows:

1. Initial Phone Screen

The first step is an initial phone screen, which usually lasts around 30 minutes. This conversation is often casual and serves as an opportunity for the recruiter to gauge your interest in Looker and the role. Expect to discuss your background, relevant experiences, and how they align with Looker's mission and values. This is also a chance for you to ask questions about the company and the team dynamics.

2. Technical Assessment

Following the initial screen, candidates may be required to complete a technical homework assignment. This assignment is designed to evaluate your analytical skills and proficiency in SQL, which is crucial for the role. After submitting the assignment, you will typically have a technical phone interview where you will be asked to solve basic SQL problems and discuss your approach to data analysis.

3. Onsite Interviews

The onsite interview process generally consists of multiple rounds, often around five to six interviews with various team members. These interviews will include a mix of technical assessments, such as SQL tests, and behavioral questions. The technical rounds will focus on your ability to analyze data using Looker and your understanding of business intelligence concepts. The behavioral interviews will assess your soft skills, teamwork, and how you handle challenges in a collaborative environment.

4. Final Interviews

In some cases, candidates may have a final round of interviews with senior leadership, such as the director or even the founder. This stage is more conversational and allows for deeper discussions about your fit within the company and your potential contributions to the team. It’s also an opportunity for you to gain insights into the company’s vision and culture.

As you prepare for your interview, be ready to engage in discussions about your experiences and how they relate to the role, as well as to ask thoughtful questions about Looker and its operations. Now, let’s delve into the specific interview questions that candidates have encountered during the process.

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

Understand the Role's Focus on SQL

As a Data Scientist at Looker, SQL proficiency is paramount. Prepare to demonstrate your understanding of SQL concepts, particularly joins (left, right, inner), aggregations, and subqueries. Familiarize yourself with Looker’s specific functionalities and how they relate to data analysis. Practicing SQL problems, especially those that mimic real-world scenarios you might encounter at Looker, will give you a significant edge.

Prepare for Behavioral Questions

Expect a mix of technical and behavioral questions during your interviews. Looker values a collaborative and friendly culture, so be ready to discuss your past experiences in teamwork, problem-solving, and how you handle challenges. Use the STAR (Situation, Task, Action, Result) method to structure your responses, ensuring you convey your thought process and the impact of your contributions.

Engage in Two-Way Conversations

Interviews at Looker are described as two-way discussions. Approach your interviews with curiosity; prepare thoughtful questions about the team dynamics, company culture, and the specific challenges the team is facing. This not only shows your interest in the role but also helps you assess if Looker is the right fit for you.

Be Ready for Technical Assessments

In addition to SQL questions, you may encounter technical assessments or homework assignments. These are designed to evaluate your analytical skills and how you approach data problems. Take these seriously; they are an opportunity to showcase your technical abilities and thought process. Practice with sample datasets and familiarize yourself with Looker’s platform to demonstrate your capability effectively.

Stay Positive and Professional

While experiences vary, some candidates have reported less-than-ideal interactions during interviews. Regardless of the interviewer's demeanor, maintain a positive and professional attitude. Your ability to stay composed and engaged can set you apart, especially if the interview feels casual or unstructured.

Follow Up Thoughtfully

After your interviews, consider sending a follow-up email thanking your interviewers for their time and reiterating your interest in the role. This not only shows professionalism but also keeps you on their radar. If you have any additional questions or thoughts that arose after the interview, feel free to include them in your follow-up.

By preparing thoroughly and approaching the interview process with a positive mindset, you can position yourself as a strong candidate for the Data Scientist role at Looker. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Scientist interview at Looker. The interview process will likely assess your technical skills, particularly in SQL, as well as your ability to analyze data and communicate insights effectively. Be prepared to discuss your experience and how it aligns with Looker's mission and products.

Technical Skills

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

Understanding SQL joins is crucial for data manipulation and analysis.

How to Answer

Clearly define both types of joins and provide a brief example of when you would use each.

Example

“A LEFT JOIN returns all records from the left table and the matched records from the right table. If there is no match, NULL values are returned for columns from the right table. Conversely, a RIGHT JOIN returns all records from the right table and the matched records from the left table. I would use a LEFT JOIN when I want to ensure I capture all entries from the primary dataset, even if there are no corresponding entries in the secondary dataset.”

2. Describe a complex SQL query you have written. What was the purpose and outcome?

This question assesses your practical experience with SQL and your problem-solving skills.

How to Answer

Discuss the context of the query, the specific challenges you faced, and how you overcame them.

Example

“I once wrote a complex SQL query to analyze customer purchase patterns over a year. The query involved multiple joins and subqueries to aggregate data by month and product category. The outcome was a detailed report that helped the marketing team tailor their campaigns, resulting in a 15% increase in sales for the targeted products.”

3. How do you approach data cleaning and preparation?

Data preparation is a critical step in any data analysis process.

How to Answer

Outline your typical workflow for data cleaning, including tools and techniques you use.

Example

“I start by assessing the dataset for missing values and outliers. I use Python libraries like Pandas for data manipulation, applying techniques such as imputation for missing values and filtering out outliers based on statistical methods. This ensures that the data is reliable and ready for analysis.”

4. What is your experience with Looker or similar BI tools?

Familiarity with BI tools is essential for this role.

How to Answer

Discuss your experience with Looker or any similar tools, focusing on how you used them to derive insights.

Example

“I have used Looker extensively in my previous role to create dashboards that visualize key performance indicators. I leveraged LookML to build custom metrics and dimensions, which allowed stakeholders to interact with the data and make informed decisions quickly.”

Behavioral Questions

1. Describe a time when you had to communicate complex data findings to a non-technical audience.

This question evaluates your communication skills and ability to simplify complex concepts.

How to Answer

Provide a specific example that highlights your ability to tailor your message to your audience.

Example

“In my last role, I presented a data analysis report to the marketing team, which included complex statistical findings. I used visual aids like charts and graphs to illustrate the trends and avoided technical jargon, focusing instead on actionable insights. This approach helped the team understand the data and implement changes effectively.”

2. How do you prioritize your tasks when working on multiple projects?

Time management is key in a fast-paced environment.

How to Answer

Explain your strategy for prioritizing tasks and managing deadlines.

Example

“I use a combination of project management tools and prioritization frameworks like the Eisenhower Matrix. I assess the urgency and importance of each task, focusing on high-impact projects first. Regular check-ins with my team also help ensure alignment and adjust priorities as needed.”

3. Can you give an example of a time you faced a significant challenge in a project? How did you overcome it?

This question assesses your problem-solving abilities and resilience.

How to Answer

Describe the challenge, your thought process, and the steps you took to resolve it.

Example

“During a project, I encountered unexpected data discrepancies that threatened our timeline. I quickly organized a meeting with the data engineering team to identify the source of the issue. By collaborating closely, we pinpointed the problem and implemented a fix, allowing us to meet our deadline without compromising the quality of our analysis.”

4. How would your friends describe you?

This question aims to gauge your self-awareness and interpersonal skills.

How to Answer

Reflect on your personal qualities and how they relate to teamwork and collaboration.

Example

“My friends would describe me as analytical and supportive. They often rely on me for advice because I take the time to listen and provide thoughtful insights. I believe these qualities help me foster a collaborative environment in the workplace, where everyone feels valued and heard.”