Unum Data Engineer Interview Questions + Guide in 2025

Unum is a leading provider of employee benefits dedicated to helping organizations create environments where employees can thrive both personally and professionally.

As a Data Engineer at Unum, you will be responsible for designing, building, and maintaining robust data systems and pipelines that optimize data utilization across the organization. Your role will require strong technical expertise in computer programming, database management, and data architecture, with a specific focus on utilizing technologies such as AWS EKS, Java Spring Boot, MongoDB, Kafka, Snowflake, and Linux. The ideal candidate will possess a solid understanding of data architecture principles and the ability to integrate large volumes of data from various sources, applying validation and reconciliation techniques to build a rich data framework.

In this role, you will collaborate closely with data scientists and business partners to create tailored data structures that address specific business challenges, providing technical leadership and mentorship to junior team members. Your professionalism and communication skills will be crucial, as you will be required to present findings and influence decision-making within the organization. A results-oriented mindset and a commitment to continuous learning will set you apart as a strong fit for Unum's culture, which values inclusion, diversity, and the advancement of its employees.

This guide will prepare you for the interview process by equipping you with insights into the role's expectations and the skills necessary to excel, ensuring you can confidently demonstrate your fit for the Data Engineer position at Unum.

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

1. Initial Phone Screen

The process begins with a phone interview, usually lasting around 30 to 45 minutes, conducted by a recruiter or HR representative. This conversation focuses on your background, experience, and motivations for applying to Unum. The recruiter may also discuss the company culture and the specifics of the role, ensuring that you understand what to expect moving forward.

2. Technical Assessment

Following the initial screen, candidates may be required to complete a technical assessment. This could involve a self-recorded video interview or an online coding challenge that tests your proficiency in relevant programming languages and data engineering concepts. Expect questions related to SQL, data architecture, and possibly some coding exercises that demonstrate your ability to design and implement data pipelines.

3. Panel Interview

The next step typically involves a panel interview, which is conducted via video conferencing tools like Microsoft Teams. This interview usually includes two or more team members, including potential managers and peers. The panel will ask a mix of technical and behavioral questions, focusing on your problem-solving abilities, experience with data technologies (such as AWS, Kafka, and Snowflake), and how you handle collaboration and conflict in a team setting.

4. Final Interview

In some cases, there may be a final interview round with senior leaders or stakeholders. This stage is designed to evaluate your strategic thinking and how well you align with Unum's business goals. You may be asked to present a case study or discuss how you would approach specific data engineering challenges relevant to the company.

Throughout the interview process, it is essential to demonstrate your technical expertise, communication skills, and ability to work collaboratively. Be prepared to discuss your past experiences in detail and how they relate to the responsibilities of the Data Engineer role at Unum.

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

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

Understand the Interview Process

Be prepared for a multi-step interview process that may include a phone screen, video panel interview, and possibly in-person interviews. Familiarize yourself with the structure of these interviews, as candidates have reported varying experiences. Knowing what to expect can help you stay calm and focused.

Emphasize Technical Proficiency

Given the technical nature of the Data Engineer role, ensure you are well-versed in the required technologies such as AWS EKS, Spring Boot, MongoDB, Kafka, Snowflake, and Linux. Brush up on your SQL skills, as complex queries are a significant part of the job. Be ready to discuss your experience with data pipelines, ETL processes, and data architecture principles in detail.

Use the STAR Method

When answering behavioral questions, utilize the STAR (Situation, Task, Action, Result) method to structure your responses. This approach allows you to clearly articulate your experiences and demonstrate your problem-solving abilities. Practice common scenarios you might encounter in a data engineering context, such as handling multiple projects or resolving conflicts within a team.

Showcase Your Communication Skills

Unum values strong communication and collaboration, especially since the role involves working with data scientists and business partners. Be prepared to discuss how you have effectively communicated complex technical concepts to non-technical stakeholders in the past. Highlight any leadership or mentorship experiences, as these will demonstrate your ability to guide and support team members.

Prepare Thoughtful Questions

At the end of your interview, you will likely have the opportunity to ask questions. Prepare insightful questions that reflect your understanding of the company’s goals and the role’s impact on those goals. Inquire about the team dynamics, ongoing projects, or how the company fosters a culture of inclusion and diversity. This shows your genuine interest in the position and the organization.

Be Yourself

While it’s important to present your qualifications, don’t forget to let your personality shine through. Candidates have reported that being authentic and relatable can make a positive impression. Unum values a supportive and inclusive culture, so showing that you align with these values can help you stand out.

Follow Up

After your interview, consider sending a thank-you email to express your appreciation for the opportunity to interview. This not only reinforces your interest in the position but also allows you to reiterate any key points you may want to emphasize. A thoughtful follow-up can leave a lasting impression on your interviewers.

By preparing thoroughly and approaching the interview with confidence and authenticity, you can position yourself as a strong candidate for the Data Engineer role at Unum. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Unum. The interview process will likely focus on your technical skills, problem-solving abilities, and how you collaborate with others. Be prepared to discuss your experience with data systems, programming languages, and your approach to data architecture.

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 management.

How to Answer

Discuss your experience with ETL processes, including the tools and technologies you used. Highlight specific projects where you successfully implemented ETL and the impact it had on data accessibility and quality.

Example

“In my previous role, I designed an ETL pipeline using AWS Glue to extract data from various sources, transform it using Python scripts, and load it into a Snowflake data warehouse. This improved our data accessibility by 40%, allowing the analytics team to generate insights more quickly.”

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

SQL proficiency is essential for data extraction and manipulation.

How to Answer

Share your experience with SQL, focusing on complex queries you’ve written. Explain the context and the outcome of your query.

Example

“I have extensive experience with SQL, including writing complex queries involving multiple joins and subqueries. For instance, I created a query that aggregated sales data across different regions and time periods, which helped the marketing team identify trends and adjust their strategies accordingly.”

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

Data quality is critical for reliable analytics and decision-making.

How to Answer

Discuss the methods and tools you use to validate and clean data. Mention any automated processes you’ve implemented to maintain data integrity.

Example

“I implement data validation checks at each stage of the ETL process, using tools like Apache Airflow to automate these checks. For example, I set up alerts for any discrepancies in data volume or unexpected null values, ensuring that only high-quality data is loaded into our systems.”

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

Familiarity with cloud platforms is increasingly important for data engineering roles.

How to Answer

Talk about your experience with AWS services relevant to data engineering, such as S3, Redshift, or EKS. Provide examples of how you’ve utilized these services in your projects.

Example

“I have worked extensively with AWS, particularly with S3 for data storage and Redshift for data warehousing. In one project, I migrated our on-premise data warehouse to Redshift, which reduced our query times by 50% and significantly lowered our operational costs.”

Problem-Solving and Collaboration

5. Can you describe a challenging data problem you faced and how you resolved it?

Problem-solving skills are essential for a Data Engineer, especially when dealing with complex data issues.

How to Answer

Share a specific example of a data challenge, the steps you took to address it, and the outcome.

Example

“I encountered a situation where our data ingestion process was failing due to schema changes in the source database. I quickly collaborated with the database team to understand the changes, updated our ETL scripts accordingly, and implemented a version control system for our data schemas to prevent similar issues in the future.”

6. How do you handle conflicts within a project team?

Collaboration and communication are key in a team environment.

How to Answer

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

Example

“When conflicts arise, I believe in addressing them directly and constructively. For instance, during a project, there was a disagreement about the data model design. I facilitated a meeting where each team member could present their perspective, and we ultimately reached a consensus that combined the best elements of both proposals.”

7. What strategies do you use to stay updated with the latest data engineering trends and technologies?

Continuous learning is vital in the fast-evolving field of data engineering.

How to Answer

Share your methods for staying informed, such as attending conferences, participating in online courses, or following industry leaders.

Example

“I regularly attend data engineering meetups and webinars, and I’m an active member of several online forums. I also take online courses to learn about new tools and technologies, such as the latest features in AWS or advancements in data processing frameworks.”

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

Time management and prioritization are essential skills for a Data Engineer.

How to Answer

Explain your approach to prioritizing tasks, including any tools or methodologies you use.

Example

“I use a combination of Agile methodologies and project management tools like Jira to prioritize my tasks. I assess the urgency and impact of each project and communicate with stakeholders to ensure alignment on priorities, which helps me manage my workload effectively.”