PwC Data Engineer Interview Questions + Guide in 2025

PwC is a global leader in professional services, offering a wide range of solutions in audit, tax, and advisory, with a strong focus on data and analytics to drive business growth.

As a Data Engineer at PwC, you will play a pivotal role in building robust data infrastructure and systems that facilitate efficient data processing and analysis. Your responsibilities will include designing and implementing data pipelines, integrating various data sources, and transforming raw data into actionable insights that empower clients to make informed decisions. You will leverage advanced technologies in cloud environments like GCP, AWS, and Azure, while ensuring compliance with data governance and security policies.

To excel in this role, you should possess strong problem-solving skills, a deep understanding of SQL and ETL processes, and proficiency in programming languages such as Python or Scala. Additionally, you should be adept at collaborating with business stakeholders to translate their data requirements into technical solutions. Your ability to manage projects, mentor team members, and communicate effectively will be crucial for delivering high-quality results that align with PwC's values of integrity, innovation, and excellence.

This guide aims to equip you with insights and strategies to prepare effectively for your interview at PwC, helping you to stand out as an ideal candidate for the Data Engineer role.

The interview process for a Data Engineer position at PwC is structured and typically consists of multiple rounds designed to assess both technical and interpersonal skills.

1. Initial Screening

The first step is an initial screening, usually conducted by a recruiter or HR representative. This round typically lasts about 30 minutes and focuses on understanding your background, skills, and motivations for applying to PwC. The recruiter will assess your fit for the role and the company culture, as well as discuss the job expectations and responsibilities.

2. Technical Assessment

Following the initial screening, candidates usually undergo a technical assessment. This may involve a coding test that focuses on SQL, Python, or other relevant programming languages. Candidates might be asked to solve problems related to data cleaning, transformation, or building data pipelines. This round is crucial as it evaluates your practical skills and understanding of data engineering concepts.

3. Technical Interviews

After successfully passing the technical assessment, candidates typically participate in one or more technical interviews. These interviews are often conducted by senior data engineers or managers and may include scenario-based questions where you are asked to design or optimize data architectures, discuss ETL processes, or explain your experience with cloud technologies like AWS, Azure, or GCP. Expect to dive deep into your past projects and demonstrate your problem-solving abilities.

4. Behavioral Interview

In addition to technical skills, PwC places a strong emphasis on cultural fit and interpersonal skills. A behavioral interview is usually conducted to assess how you work within a team, handle conflicts, and align with PwC's values. You may be asked to provide examples of how you've led projects, mentored team members, or navigated complex situations in previous roles.

5. Final Interview

The final round often involves a discussion with higher-level management, such as a Partner or Director. This interview may cover both technical and behavioral aspects, but it will also focus on your long-term career goals, leadership potential, and how you can contribute to PwC's mission. This round is an opportunity for you to ask questions about the company and the team you would be joining.

As you prepare for your interview, consider the specific skills and experiences that PwC values in a Data Engineer, as well as the types of questions you might encounter in each round.

Next, let's explore the specific interview questions that candidates have faced during the process.

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

Understand the Interview Structure

The interview process at PwC for a Data Engineer typically consists of multiple rounds, including an HR interview, coding assessments, and technical interviews with managers and directors. Familiarize yourself with this structure and prepare accordingly. For instance, expect to demonstrate your SQL skills in coding rounds and be ready to discuss your previous projects in detail during the final interviews.

Prepare for Technical Assessments

Given the emphasis on technical skills, particularly in SQL, Python, and cloud technologies, ensure you are well-versed in these areas. Practice coding problems that involve data cleaning, transformation, and building ETL pipelines. Be prepared to discuss specific tools and technologies you have used, such as Google Cloud Platform (GCP) services, and how they relate to the projects you've worked on.

Showcase Your Problem-Solving Skills

During the interviews, you may be presented with scenario-based questions that require you to demonstrate your problem-solving abilities. Use the STAR (Situation, Task, Action, Result) method to structure your responses. Highlight how you approached complex problems in your previous roles, the actions you took, and the outcomes of those actions.

Align with PwC's Values

PwC places a strong emphasis on its values, including integrity, teamwork, and excellence. Be prepared to discuss how your personal values align with those of the firm. Reflect on past experiences where you demonstrated these values, particularly in collaborative settings or when facing ethical dilemmas.

Communicate Clearly and Effectively

Effective communication is crucial, especially when discussing technical concepts with non-technical stakeholders. Practice explaining complex ideas in simple terms. During the interview, ensure you articulate your thoughts clearly and engage with your interviewers by asking insightful questions about the role and the team.

Emphasize Leadership and Mentorship

As a Data Engineer at PwC, you may be expected to take on leadership roles and mentor junior team members. Be ready to discuss your experiences in leading projects, coaching others, and fostering a collaborative team environment. Highlight specific instances where you motivated your team or contributed to their professional development.

Be Ready for Behavioral Questions

Expect behavioral questions that assess your fit within the company culture. Prepare examples that showcase your adaptability, resilience, and ability to work under pressure. Reflect on how you have navigated challenges in past roles and what you learned from those experiences.

Follow Up with Thoughtful Questions

At the end of your interview, you will likely have the opportunity to ask questions. Use this time to inquire about the team dynamics, ongoing projects, and how success is measured in the role. This not only shows your interest in the position but also helps you gauge if PwC is the right fit for you.

By following these tips and preparing thoroughly, you will position yourself as a strong candidate for the Data Engineer role at PwC. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at PwC. The interview process will assess your technical skills, problem-solving abilities, and cultural fit within the organization. Be prepared to discuss your experience with data architecture, ETL processes, and cloud technologies, as well as your approach to teamwork and leadership.

Technical Skills

1. Can you describe an end-to-end ETL process you have implemented in a previous role?

This question aims to assess your practical experience with ETL processes and your ability to articulate complex technical workflows.

How to Answer

Provide a clear overview of the ETL process, including the tools used, the data sources, and the transformations applied. Highlight any challenges faced and how you overcame them.

Example

“In my previous role, I designed an ETL process using Apache NiFi to extract data from various sources, including SQL databases and APIs. I transformed the data using Python scripts to clean and aggregate it before loading it into a Snowflake data warehouse. One challenge was ensuring data quality, which I addressed by implementing validation checks at each stage of the process.”

2. What is your experience with SQL, and can you provide an example of a complex query you wrote?

This question evaluates your SQL proficiency and your ability to handle complex data retrieval tasks.

How to Answer

Discuss your experience with SQL, focusing on specific functions or techniques you have used. Provide a brief example of a complex query, explaining its purpose and outcome.

Example

“I have extensive experience with SQL, particularly in writing complex queries involving multiple joins and subqueries. For instance, I wrote a query to analyze customer purchase patterns by joining sales data with customer demographics, which helped the marketing team target specific segments more effectively.”

3. How do you ensure data quality and integrity in your data pipelines?

This question assesses your understanding of data governance and quality assurance practices.

How to Answer

Discuss the strategies and tools you use to monitor and maintain data quality throughout the data pipeline.

Example

“I implement data validation checks at various stages of the pipeline, such as schema validation and data type checks. Additionally, I use tools like Great Expectations to automate data quality testing and alert the team to any anomalies, ensuring that we maintain high data integrity.”

4. Can you explain the differences between batch processing and real-time processing?

This question tests your understanding of data processing methodologies.

How to Answer

Clearly define both concepts and discuss scenarios where each would be appropriate.

Example

“Batch processing involves collecting and processing data in large groups at scheduled intervals, which is suitable for tasks like monthly reporting. In contrast, real-time processing handles data as it arrives, making it ideal for applications like fraud detection where immediate action is required.”

5. What cloud technologies have you worked with, and how have you utilized them in your projects?

This question evaluates your familiarity with cloud platforms and their services.

How to Answer

Mention specific cloud technologies you have experience with and describe how you have applied them in your work.

Example

“I have worked extensively with Google Cloud Platform, particularly BigQuery for data warehousing and Dataflow for stream processing. In a recent project, I used Dataflow to process real-time data from IoT devices, allowing us to analyze and visualize the data in near real-time using Google Data Studio.”

Behavioral Questions

1. Describe a time when you had to lead a team through a challenging project.

This question assesses your leadership and teamwork skills.

How to Answer

Share a specific example that highlights your leadership style and how you motivated your team to overcome challenges.

Example

“I led a team during a critical data migration project where we faced tight deadlines and technical issues. I organized daily stand-up meetings to address concerns and keep everyone aligned. By fostering open communication and encouraging team members to share their ideas, we successfully completed the migration ahead of schedule.”

2. How do you handle conflicts within a team?

This question evaluates your conflict resolution skills and ability to maintain a positive team dynamic.

How to Answer

Discuss your approach to conflict resolution, emphasizing communication and collaboration.

Example

“When conflicts arise, I believe in addressing them directly and promptly. I facilitate a discussion between the parties involved, encouraging them to express their viewpoints. By focusing on finding common ground and working towards a solution, I help maintain a collaborative team environment.”

3. Can you give an example of how you have contributed to a culture of continuous improvement in your team?

This question assesses your commitment to professional development and team growth.

How to Answer

Share specific initiatives or practices you have implemented to foster a culture of learning and improvement.

Example

“I initiated a bi-weekly knowledge-sharing session where team members could present new tools or techniques they had learned. This not only enhanced our collective skill set but also encouraged collaboration and innovation within the team.”

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

This question evaluates your time management and organizational skills.

How to Answer

Discuss your approach to prioritization, including any tools or methods you use.

Example

“I use a combination of project management tools like Trello and the Eisenhower Matrix to prioritize tasks based on urgency and importance. This helps me focus on high-impact activities while ensuring that I meet deadlines across multiple projects.”

5. What motivates you to excel in your role as a Data Engineer?

This question assesses your passion for the field and your drive for success.

How to Answer

Share your motivations and how they align with the goals of the organization.

Example

“I am motivated by the challenge of transforming complex data into actionable insights that drive business decisions. The opportunity to work with cutting-edge technologies and collaborate with diverse teams at PwC excites me, as I believe it allows me to make a meaningful impact on our clients’ success.”