Aon Data Engineer Interview Questions + Guide in 2025

Aon is a leading global professional services firm providing a broad range of risk, retirement, and health solutions.

As a Data Engineer at Aon, you will be instrumental in designing, developing, and maintaining robust data architectures that facilitate efficient data flow across the organization. Your role will involve collaborating with cross-functional teams, including data scientists and analysts, to understand their data requirements and optimize data processes for improved efficiency. You will be expected to utilize cutting-edge integration and data management tools, such as StreamSets, Amazon S3, and Snowflake, while ensuring data security, integrity, and availability. The ideal candidate will possess a strong technical background, with expertise in programming languages such as SQL and Python, as well as familiarity with big data file formats and data integration processes. A successful Data Engineer at Aon will not only have the technical skills to navigate complex datasets but also the problem-solving abilities and communication skills to present findings effectively to stakeholders.

This guide will help you prepare for your interview by providing insights into the key responsibilities and skills that Aon values in their Data Engineers, allowing you to showcase your fit for the role and the company's culture.

The interview process for a Data Engineer position at Aon is structured to assess both technical skills and cultural fit within the organization. It typically consists of several key stages:

1. Initial HR Screening

The first step in the interview process is a phone screening with a Human Resources representative. This conversation usually lasts around 30 minutes and focuses on your background, experience, and motivations for applying to Aon. The HR representative will also provide insights into the company culture and the specifics of the Data Engineer role, ensuring that you understand the expectations and opportunities available.

2. Hiring Manager Discussion

Following the initial screening, candidates will have a discussion with the hiring manager. This round is more in-depth and allows you to showcase your technical expertise and problem-solving abilities. The hiring manager will likely ask about your previous projects, your approach to data engineering challenges, and how you collaborate with cross-functional teams. This is also an opportunity for you to ask questions about the team dynamics and the projects you would be working on.

3. Technical Interview

The technical interview is a critical component of the process, where candidates are assessed on their technical skills and knowledge relevant to data engineering. This may include a coding test, where you will be asked to solve SQL problems or demonstrate your proficiency in programming languages such as Python or Scala. Additionally, expect questions related to data architecture, ETL processes, and cloud technologies like AWS, as well as discussions about your experience with big data file formats and data security practices.

4. Onsite Interview

The final stage typically involves an onsite interview, which may be conducted virtually. This round consists of multiple one-on-one interviews with team members and other stakeholders. Each session will focus on different aspects of the role, including technical skills, problem-solving abilities, and behavioral questions. You may also be asked to participate in a practical coding exercise or case study that reflects real-world scenarios you would encounter as a Data Engineer at Aon.

As you prepare for these interviews, it's essential to be ready for a variety of questions that will test your technical knowledge and your ability to work collaboratively in a team environment.

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 Engineer at Aon. Familiarize yourself with the specific technologies mentioned in the job description, such as StreamSets, Amazon S3, Snowflake, and Databricks. Reflect on how your previous experiences align with the role's requirements, particularly in designing and maintaining data architectures. This will not only help you answer questions more effectively but also demonstrate your genuine interest in the position.

Prepare for Technical Assessments

Given that the interview process includes a technical discussion and coding test, it’s crucial to brush up on your SQL, Python, and Apache Spark skills. Practice solving moderate difficulty SQL problems, focusing on data manipulation and optimization techniques. Additionally, be prepared to discuss your experience with ETL/ELT processes and how you have approached troubleshooting data pipelines in the past. Familiarity with big data file formats like Avro and Parquet will also be beneficial.

Showcase Collaboration Skills

Aon emphasizes collaboration with cross-functional teams, so be ready to discuss your experiences working with data scientists, analysts, and other stakeholders. Prepare examples that highlight your ability to communicate complex technical concepts to non-technical team members. This will demonstrate your interpersonal skills and your understanding of the importance of teamwork in achieving business objectives.

Emphasize Data Security and Governance

Data security and governance are critical components of the Data Engineer role at Aon. Be prepared to discuss your knowledge and experience in these areas. Share specific examples of how you have ensured data integrity and security in your previous roles. This will show that you are not only technically proficient but also aware of the broader implications of data management.

Be Ready for Behavioral Questions

Expect behavioral questions that assess your problem-solving abilities and adaptability. Use the STAR (Situation, Task, Action, Result) method to structure your responses. Highlight instances where you faced challenges in data processing or architecture and how you overcame them. This will help interviewers gauge your critical thinking and resilience.

Align with Company Culture

Aon values diversity, innovation, and a continuous learning culture. During your interview, express your enthusiasm for working in an inclusive environment and your commitment to personal and professional growth. Share any experiences that reflect your adaptability and willingness to embrace new technologies or methodologies. This alignment with Aon’s culture will strengthen your candidacy.

Ask Insightful Questions

Prepare thoughtful questions to ask your interviewers. Inquire about the team dynamics, ongoing projects, and how Aon supports continuous learning and innovation. This not only shows your interest in the role but also helps you assess if Aon is the right fit for you. Engaging in a two-way conversation can leave a positive impression on your interviewers.

By following these tips, you will be well-prepared to showcase your skills and fit for the Data Engineer role at Aon. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Aon. The interview process will likely assess your technical skills, problem-solving abilities, and your experience with data architecture and integration. Be prepared to discuss your past projects and how you have collaborated with cross-functional teams.

Technical Skills

1. Can you explain the ETL process and how you have implemented it in your previous projects?

Understanding the ETL (Extract, Transform, Load) process is crucial for a Data Engineer, as it is fundamental to data integration and management.

How to Answer

Discuss your experience with ETL tools and frameworks, emphasizing specific projects where you designed or optimized ETL processes. Highlight any challenges you faced and how you overcame them.

Example

“In my previous role, I implemented an ETL process using Apache NiFi to extract data from various sources, transform it using Python scripts, and load it into a Snowflake data warehouse. This process improved data availability by 30% and reduced the time taken for data processing by 40%.”

2. What experience do you have with big data technologies, such as Hadoop or Spark?

Familiarity with big data technologies is essential for handling large datasets effectively.

How to Answer

Share specific experiences where you utilized big data technologies, focusing on the tools you used and the outcomes of your projects.

Example

“I have worked extensively with Apache Spark for data processing tasks. In one project, I used PySpark to process terabytes of data from our logs, which allowed us to derive insights that improved our application performance by 25%.”

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

Data quality is critical in data engineering, and interviewers will want to know your approach to maintaining it.

How to Answer

Discuss the methods and tools you use to validate and monitor data quality, as well as any specific metrics you track.

Example

“I implement data validation checks at each stage of the ETL process, using tools like Great Expectations to ensure data quality. Additionally, I set up monitoring alerts to catch any anomalies in real-time, which has helped maintain a 99.9% data accuracy rate.”

4. Describe your experience with cloud platforms, particularly AWS.

As Aon utilizes cloud technologies, familiarity with AWS services is a significant advantage.

How to Answer

Detail your experience with AWS services relevant to data engineering, such as S3, Redshift, or Glue, and how you have leveraged them in your projects.

Example

“I have utilized AWS S3 for data storage and AWS Glue for ETL processes. In a recent project, I set up a data lake on S3, which allowed our data scientists to access clean, structured data quickly, leading to faster model development cycles.”

5. Can you explain the difference between structured and unstructured data?

Understanding data types is fundamental for a Data Engineer, especially when designing data architectures.

How to Answer

Define both types of data and provide examples of how you have worked with each in your previous roles.

Example

“Structured data is organized and easily searchable, like data in relational databases, while unstructured data includes formats like text, images, and videos. In my last project, I developed a pipeline to process unstructured data from social media feeds, which we then analyzed for sentiment analysis.”

Problem-Solving and Analytical Skills

1. Describe a challenging data problem you faced and how you resolved it.

This question assesses your problem-solving skills and ability to think critically under pressure.

How to Answer

Choose a specific example that highlights your analytical skills and the steps you took to resolve the issue.

Example

“In a previous project, we faced performance issues with our data pipeline due to inefficient queries. I conducted a root cause analysis, identified bottlenecks, and optimized our SQL queries, which improved the pipeline's performance by 50%.”

2. How do you approach troubleshooting data pipeline failures?

Interviewers want to know your systematic approach to identifying and resolving issues.

How to Answer

Explain your troubleshooting process, including the tools and techniques you use to diagnose and fix problems.

Example

“When a data pipeline fails, I first check the logs to identify the error messages. I then replicate the issue in a test environment to understand the root cause. For instance, I once discovered a schema mismatch that was causing failures, which I resolved by updating the transformation logic.”

3. What strategies do you use to optimize data processing performance?

Performance optimization is key in data engineering, and interviewers will look for your strategies.

How to Answer

Discuss specific techniques you have employed to enhance data processing efficiency, such as indexing, partitioning, or caching.

Example

“I often use partitioning in our data warehouse to improve query performance. For example, I partitioned our sales data by date, which reduced query times significantly, allowing our analysts to access insights much faster.”

4. How do you stay updated with emerging data technologies?

This question assesses your commitment to continuous learning and professional development.

How to Answer

Share the resources you use to keep your skills current, such as online courses, webinars, or industry conferences.

Example

“I regularly attend webinars and follow industry leaders on platforms like LinkedIn. I also participate in online courses on platforms like Coursera to learn about new tools and technologies, such as the latest features in Apache Spark.”

5. Can you discuss a time when you had to collaborate with data scientists or analysts?

Collaboration is essential in data engineering, and interviewers want to know how you work with others.

How to Answer

Provide an example that illustrates your ability to communicate effectively and work as part of a team.

Example

“In a recent project, I collaborated with data scientists to understand their data needs for a machine learning model. I gathered their requirements and designed a data pipeline that provided them with clean, structured data, which ultimately improved the model's accuracy by 15%.”