Securian Financial Group Data Engineer Interview Questions + Guide in 2025

Securian Financial Group is a leading provider of insurance and financial services, committed to helping its customers achieve financial security and peace of mind.

The Data Engineer role at Securian Financial is pivotal in designing, deploying, and managing the organization's data architecture. This involves collaborating with technology and management teams to define standards for data storage, consumption, integration, and management, ultimately translating these requirements into a coherent blueprint. Key responsibilities include building and maintaining complex data pipelines, ensuring data accuracy, and implementing robust data management practices. Success in this role requires advanced knowledge of data engineering technologies, hands-on experience with AWS cloud services, and proficiency in programming languages such as Java, Python, or SQL. Additionally, candidates should possess strong problem-solving abilities, excellent communication skills, and the capacity to work effectively in cross-functional teams. A proactive approach to continuous improvement and mentorship of junior engineers is also essential.

This guide aims to equip you with the insights and strategies needed to excel in your Securian Financial Data Engineer interview, helping you to highlight your relevant experience and demonstrate your alignment with the company’s values and expectations.

The interview process for a Data Engineer at Securian Financial Group is structured to assess both technical and interpersonal skills, ensuring candidates are well-suited for the role and the company culture.

1. Initial Screening

The process begins with an initial screening interview, typically conducted by a recruiter. This conversation lasts about 30-60 minutes and focuses on your background, qualifications, and interest in the position. The recruiter will also provide insights into the company culture and the specifics of the Data Engineer role. Expect to discuss your experience with data engineering tasks, including data pipelines, ETL processes, and cloud services.

2. Technical Interview

Following the initial screening, candidates will participate in a technical interview, which may be conducted via video conferencing. This round usually involves a technical engineer or a hiring manager who will assess your proficiency in relevant programming languages (such as SQL, Python, or Java) and your experience with AWS services. You may be asked to solve coding problems or discuss your previous projects in detail, particularly those that demonstrate your ability to build and maintain data architectures.

3. Behavioral Interview

The next step is a behavioral interview, where you will meet with the hiring manager or a senior team member. This interview focuses on your soft skills, such as communication, teamwork, and problem-solving abilities. Expect questions that require you to provide specific examples from your past experiences, particularly in situations that demonstrate your ability to work collaboratively in a cross-functional team or lead initiatives.

4. Panel Interview

In some cases, candidates may be invited to a panel interview, which consists of multiple interviewers from different levels within the organization. This round is designed to evaluate how well you can articulate your thoughts and respond to questions from various perspectives. The panel may include members from the data engineering team, project management, and other relevant departments. Be prepared to discuss your approach to data governance, security, and quality assurance.

5. Final Interview

The final interview is often with a senior leader or executive within the company. This round is less technical and more focused on cultural fit and alignment with Securian Financial's values. You may be asked about your long-term career goals, your understanding of the financial services industry, and how you can contribute to the company's mission.

6. Assessment

Some candidates may also be required to complete a technical assessment or a personality test as part of the interview process. This assessment helps the company gauge your technical skills and how you might fit within the team dynamics.

As you prepare for your interviews, consider the following questions that have been commonly asked during the process.

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

Embrace a Conversational Approach

Interviews at Securian Financial tend to be conversational rather than strictly formal. This means you should aim to engage in a dialogue rather than just answering questions. Be prepared to share your experiences in a narrative format, focusing on how your background aligns with the role. This approach not only showcases your skills but also allows you to connect with the interviewers on a personal level.

Highlight Your Technical Expertise

Given the emphasis on data engineering tasks, ensure you can discuss your experience with data pipelines, ETL processes, and AWS services in detail. Be ready to provide specific examples of projects where you utilized tools like Apache Airflow or AWS Glue. Demonstrating your technical knowledge and problem-solving skills will be crucial, especially when discussing complex assignments or challenges you've faced in previous roles.

Prepare for Behavioral Questions

Expect a range of behavioral questions that assess your soft skills and how you handle various situations. Prepare to discuss scenarios where you demonstrated leadership, teamwork, and problem-solving abilities. Use the STAR (Situation, Task, Action, Result) method to structure your responses, ensuring you convey the impact of your actions clearly.

Understand the Company Culture

Securian Financial values collaboration and continuous improvement. Familiarize yourself with their hybrid work model and how it fosters teamwork. Be prepared to discuss how you can contribute to a culture of knowledge sharing and mentorship, especially if you have experience guiding junior engineers.

Ask Insightful Questions

At the end of your interviews, take the opportunity to ask thoughtful questions that reflect your interest in the role and the company. Inquire about the team dynamics, ongoing projects, or how the company is adapting to industry trends. This not only shows your enthusiasm but also helps you gauge if the company aligns with your career goals.

Be Authentic and Show Enthusiasm

Finally, be yourself. Securian Financial appreciates authenticity and a genuine passion for the work. Share what excites you about the role and how you envision contributing to the team. Your enthusiasm can set you apart from other candidates and leave a lasting impression on your interviewers.

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

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Securian Financial Group. The interview process will likely focus on your technical skills, problem-solving abilities, and experience with data architecture and management. Be prepared to discuss your past projects, your approach to data engineering tasks, and how you collaborate with cross-functional teams.

Technical Skills

1. Can you describe your experience with AWS services, particularly EC2, RDS, and S3?

Understanding your hands-on experience with AWS is crucial, as it is a key requirement for this role.

How to Answer

Discuss specific projects where you utilized these services, focusing on the challenges you faced and how you overcame them.

Example

“I have worked extensively with AWS, particularly with EC2 for hosting applications, RDS for managing relational databases, and S3 for data storage. In my last project, I set up an EC2 instance to run a data processing application that ingested data from S3, which improved our data retrieval times by 30%.”

2. What is your approach to building and maintaining data pipelines?

This question assesses your understanding of data flow and pipeline management.

How to Answer

Explain your methodology for designing, implementing, and monitoring data pipelines, including any tools you use.

Example

“I follow a structured approach to building data pipelines, starting with requirements gathering, followed by designing the architecture using tools like Apache Airflow. I ensure that the pipelines are robust by implementing error handling and logging mechanisms, which allows for easier troubleshooting.”

3. How do you ensure data quality and accuracy in your projects?

Data quality is paramount in data engineering, and this question evaluates your strategies for maintaining it.

How to Answer

Discuss the techniques you use for data validation, cleansing, and monitoring.

Example

“I implement data validation checks at various stages of the pipeline to ensure accuracy. For instance, I use automated scripts to compare incoming data against predefined standards and perform regular audits to identify anomalies.”

4. Can you explain your experience with ETL processes?

ETL (Extract, Transform, Load) is a fundamental aspect of data engineering, and your experience here is critical.

How to Answer

Provide details about the ETL tools you’ve used and the processes you’ve implemented.

Example

“I have extensive experience with ETL processes using AWS Glue and StreamSets. In my previous role, I designed an ETL pipeline that transformed raw data from multiple sources into a structured format for analysis, which significantly improved our reporting capabilities.”

5. Describe a complex data model you have designed.

This question assesses your ability to create and manage data models.

How to Answer

Talk about the purpose of the model, the challenges you faced, and the impact it had on the organization.

Example

“I designed a complex data model for a financial reporting system that integrated data from various departments. The challenge was ensuring that the model could handle both structured and unstructured data. By using dimensional modeling techniques, I was able to create a flexible model that improved our reporting accuracy by 25%.”

Problem-Solving and Collaboration

1. Tell us about a time you resolved a high-complexity issue in a project.

This question evaluates your problem-solving skills and ability to handle challenges.

How to Answer

Describe the issue, your approach to resolving it, and the outcome.

Example

“In a previous project, we faced a significant data inconsistency issue that affected our analytics. I led a root-cause analysis, identified the source of the problem in our data ingestion process, and implemented a new validation step that resolved the issue and improved our data integrity.”

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

This question assesses your organizational skills and ability to manage time effectively.

How to Answer

Explain your prioritization strategy and any tools you use to manage your workload.

Example

“I prioritize tasks based on project deadlines and the impact on the business. I use project management tools like Jira to track progress and ensure that I’m focusing on high-impact tasks first, which helps me stay organized and efficient.”

3. Describe your experience working with cross-functional teams.

Collaboration is key in data engineering, and this question evaluates your teamwork skills.

How to Answer

Discuss specific instances where you collaborated with other teams and the outcomes of those collaborations.

Example

“I frequently collaborate with data scientists and business analysts to understand their data needs. In one project, I worked closely with the analytics team to refine our data models, which resulted in a more user-friendly reporting interface that was well-received by stakeholders.”

4. Can you provide an example of a time you had to mentor a junior engineer?

This question assesses your leadership and mentoring abilities.

How to Answer

Share your approach to mentoring and the impact it had on the junior engineer’s development.

Example

“I mentored a junior data engineer who was struggling with ETL processes. I provided hands-on training and resources, which helped him gain confidence and improve his skills. As a result, he successfully led a small project on his own within a few months.”

5. How do you stay updated with industry trends and technologies?

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

How to Answer

Discuss the resources you use to keep your skills current and how you apply new knowledge.

Example

“I regularly attend webinars and follow industry blogs to stay informed about the latest trends in data engineering. I also participate in online courses to learn new tools and technologies, which I then apply in my projects to enhance our data processes.”