Public Storage Data Engineer Interview Questions + Guide in 2025

Public Storage is the largest owner and operator of self-storage facilities in the world, recognized for its exceptional workplace culture and commitment to employee growth.

As a Data Engineer at Public Storage, you will play a vital role in ensuring the integrity and efficiency of the company's data infrastructure. Your responsibilities will include collaborating with data scientists and engineers to optimize workflows, planning and implementing system enhancements, and constructing data pipelines from various sources. You will also manage the data lake, ensuring it is filled with high-quality data while providing support for machine learning operations. Key skills required for this role include proficiency in SQL and Python, as well as experience in deploying production-grade code in cloud environments. A strong foundation in relational database modeling and ETL architecture is essential, as is the ability to promote best coding practices and maintain comprehensive documentation.

This guide will help you prepare for the interview by aligning your skills and experiences with the expectations of the role, ensuring you're ready to demonstrate how you can contribute to the success of Public Storage.

The interview process for a Data Engineer at Public Storage is designed to assess both technical skills and cultural fit within the organization. It typically consists of several stages, each focusing on different aspects of the candidate's qualifications and experiences.

1. Initial Recruiter Screen

The process begins with a 30-minute phone interview with a recruiter. This initial conversation serves to gauge your interest in the role and the company, as well as to discuss your background and experiences. The recruiter will also provide insights into the company culture and the expectations for the Data Engineer position. This is an opportunity for you to ask questions about the role and the team dynamics.

2. Technical Interview

Following the recruiter screen, candidates usually participate in a technical interview, which may be conducted via video conferencing tools. This interview focuses on your technical expertise, particularly in areas such as SQL, Python, and data pipeline development. You may be asked to solve problems related to data management, ETL processes, and system enhancements. Expect to discuss your previous projects and how you approached various technical challenges.

3. Take-Home Challenge

Candidates who perform well in the technical interview may be given a take-home challenge. This task is designed to evaluate your practical skills in a real-world scenario. You will be required to complete a project that demonstrates your ability to construct and manage data pipelines, optimize workflows, and ensure data quality. After submitting your work, you will likely have a follow-up discussion to walk through your solution and thought process.

4. Final Interviews with Team Members

The final stage typically involves one-on-one interviews with team members, including senior engineers and possibly leadership. These interviews delve deeper into your technical skills, collaboration abilities, and alignment with the company's values. You may be asked situational questions that assess how you would handle specific challenges in the role, as well as your long-term career aspirations.

Throughout the interview process, Public Storage emphasizes a collegial and supportive environment, so be prepared to engage in discussions that reflect your teamwork and communication skills.

Next, let's explore the types of questions you might encounter during this interview process.

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Public Storage. The interview process will likely focus on your technical skills, problem-solving abilities, and your understanding of data management and engineering principles. Be prepared to discuss your experience with data pipelines, SQL, and cloud environments, as well as your approach to collaboration and system enhancements.

Technical Skills

1. Can you describe your experience with building and maintaining data pipelines?

This question assesses your hands-on experience with data pipeline development and management.

How to Answer

Discuss specific projects where you constructed data pipelines, the tools you used, and the challenges you faced. Highlight your understanding of data flow and transformation processes.

Example

“In my previous role, I built a data pipeline using Apache Airflow to automate the extraction, transformation, and loading of data from various sources into our data warehouse. This involved setting up scheduled jobs and ensuring data quality through validation checks, which significantly reduced manual processing time.”

2. What strategies do you use for optimizing SQL queries?

This question evaluates your SQL proficiency and your ability to enhance performance.

How to Answer

Explain your approach to query optimization, including indexing, query structure, and analyzing execution plans. Provide examples of how your optimizations improved performance.

Example

“I typically start by analyzing the execution plan of a query to identify bottlenecks. For instance, I once optimized a slow-running report by adding appropriate indexes and rewriting the query to reduce the number of joins, which improved its execution time by over 50%.”

3. How do you ensure data quality in your data lake?

This question focuses on your understanding of data management practices.

How to Answer

Discuss the methods you implement to maintain data integrity and quality, such as validation checks, monitoring, and data cleansing processes.

Example

“I implement a series of validation checks during the ETL process to ensure data quality. For example, I use automated scripts to check for duplicates and null values before data is ingested into the data lake, which helps maintain high-quality data for analysis.”

4. Describe your experience with ETL tools. Which ones have you used?

This question assesses your familiarity with ETL processes and tools.

How to Answer

Mention the ETL tools you have experience with, your role in using them, and any specific projects where you applied these tools.

Example

“I have extensive experience with Apache Airflow and DBT for ETL processes. In my last project, I used Airflow to orchestrate data workflows, ensuring timely data availability for our analytics team, while DBT was used for transforming data in our data warehouse.”

5. Can you explain the concept of data warehousing and its importance?

This question tests your foundational knowledge of data warehousing.

How to Answer

Provide a clear definition of data warehousing and discuss its significance in data analysis and reporting.

Example

“Data warehousing is the process of collecting and managing data from various sources to provide meaningful business insights. It’s crucial because it allows organizations to consolidate data for analysis, enabling better decision-making and strategic planning.”

Collaboration and Culture Fit

1. How do you approach collaboration with data scientists and other teams?

This question evaluates your teamwork and communication skills.

How to Answer

Discuss your experience working with cross-functional teams and how you ensure effective communication and collaboration.

Example

“I prioritize regular check-ins and open communication with data scientists and other stakeholders. For instance, I set up bi-weekly meetings to discuss project progress and gather feedback, which helps align our goals and ensures that the data infrastructure meets their analytical needs.”

2. What motivates you to work in a data engineering role?

This question seeks to understand your passion for the field.

How to Answer

Share your enthusiasm for data engineering and how it aligns with your career goals.

Example

“I am passionate about transforming raw data into actionable insights. The challenge of building efficient data systems and the opportunity to work on innovative projects in a collaborative environment motivate me to excel in this field.”

3. Describe a challenging project you worked on and how you overcame obstacles.

This question assesses your problem-solving skills and resilience.

How to Answer

Provide a specific example of a challenging project, the obstacles you faced, and the strategies you used to overcome them.

Example

“In a previous project, we faced significant delays due to data inconsistencies. I took the initiative to implement a data validation framework that identified issues early in the ETL process, allowing us to resolve them quickly and keep the project on track.”

4. How do you stay updated with the latest trends in data engineering?

This question gauges your commitment to professional development.

How to Answer

Discuss the resources you use to stay informed about industry trends, such as online courses, webinars, or professional networks.

Example

“I regularly attend webinars and follow industry blogs to stay updated on the latest data engineering trends. Additionally, I participate in online forums and local meetups to exchange knowledge with other professionals in the field.”

5. What are your long-term career goals in data engineering?

This question explores your career aspirations and alignment with the company’s growth.

How to Answer

Share your career goals and how they relate to the opportunities available at Public Storage.

Example

“My long-term goal is to become a lead data engineer, where I can mentor junior engineers and drive strategic data initiatives. I believe Public Storage’s commitment to innovation and professional growth aligns perfectly with my aspirations.”