Huntington National Bank Data Engineer Interview Questions + Guide in 2025

Huntington National Bank is a prominent regional bank holding company headquartered in Columbus, Ohio, committed to providing a wide range of financial services across eleven states.

The Data Engineer role at Huntington National Bank is crucial for the development and maintenance of the bank's data infrastructure. This position involves designing, building, and managing data pipelines that ensure the integrity and availability of data used for various banking operations. Key responsibilities include architecting data solutions to support business requirements, integrating data from multiple sources, and ensuring data quality and consistency. Candidates will be expected to have a strong proficiency in SQL and programming languages such as Python, as well as experience in cloud data solutions and data management practices. A collaborative mindset is essential, as the role requires working closely with cross-functional teams, including business owners and analysts, to refine data requirements and drive automation in data processes.

This guide aims to help you prepare for an interview with Huntington National Bank by outlining the expectations and skills relevant to the Data Engineer position, allowing you to present your best self during the interview process.

The interview process for a Data Engineer position at Huntington National Bank is structured to assess both technical skills and cultural fit within the organization. It typically consists of several rounds, each designed to evaluate different aspects of your qualifications and experiences.

1. Initial Phone Interview

The process begins with a phone interview, usually conducted by a member of the Human Resources team. This initial conversation lasts about 30 minutes and focuses on your background, experiences, and motivations for applying to Huntington. Expect to discuss your resume in detail, as the interviewer will want to understand your previous projects and the technical concepts you employed. This is also an opportunity for you to learn about the company culture and the expectations for the role.

2. Technical Interview

Following the initial screen, candidates typically participate in one or two technical interviews. These interviews are often conducted by hiring managers or senior data engineers and may be held in person or via video conferencing. During this stage, you will be asked to demonstrate your technical knowledge, particularly in areas such as SQL, data pipeline architecture, and cloud technologies. Be prepared to explain your approach to data management, integration, and any relevant projects you have worked on. The interviewers will likely focus on your problem-solving skills and your ability to articulate complex technical concepts clearly.

3. Behavioral Interview

In addition to technical assessments, candidates will also undergo a behavioral interview. This round is designed to evaluate how well you align with Huntington's values and teamwork-oriented culture. Expect questions that explore your past experiences in collaborative environments, your approach to challenges, and your long-term career aspirations. The interviewers will be interested in understanding how you work with others and how you contribute to a positive team dynamic.

4. Final Interview

The final stage of the interview process may involve a meeting with senior leadership or department heads. This round is less technical and more focused on your fit within the organization and your vision for the role. You may be asked about your understanding of the banking industry, your interest in the position, and how you plan to contribute to the team’s goals. This is also a chance for you to ask any remaining questions about the company and the role.

As you prepare for your interviews, it’s essential to be ready to discuss your technical skills and experiences in detail, as well as to demonstrate your enthusiasm for working at Huntington National Bank.

Next, let’s delve into the specific interview questions that candidates have encountered during the process.

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

Highlight Your Technical Expertise

As a Data Engineer, your technical skills will be under scrutiny. Be prepared to discuss your experience with SQL, Python, and data pipeline orchestration in detail. Review your past projects and be ready to explain the architecture, the challenges you faced, and the solutions you implemented. This will not only demonstrate your technical proficiency but also your problem-solving abilities. Make sure to articulate how you have utilized these skills in real-world scenarios, especially in cloud environments, as this is a key focus for Huntington.

Prepare for Behavioral Questions

Huntington values teamwork and collaboration, so expect behavioral questions that assess your ability to work within a team. Reflect on your past experiences where you successfully collaborated with others, resolved conflicts, or contributed to a team project. Use the STAR (Situation, Task, Action, Result) method to structure your responses, ensuring you convey your role and the impact of your contributions clearly.

Understand the Company Culture

During your interviews, you will likely be asked about your understanding of Huntington's culture. Familiarize yourself with their values and mission, and think about how your personal values align with theirs. Be prepared to discuss why you want to work at Huntington specifically and how you can contribute to their goals. Showing that you have done your homework will demonstrate your genuine interest in the company.

Be Ready to Discuss Your Resume

Interviewers at Huntington will focus heavily on your resume and past projects. Be prepared to discuss each item in detail, including the technologies you used, the challenges you faced, and the outcomes of your projects. This is your opportunity to showcase your experience and how it relates to the role you are applying for. Make sure to connect your past experiences to the specific requirements of the Data Engineer position.

Ask Insightful Questions

Prepare thoughtful questions to ask your interviewers. This not only shows your interest in the role but also gives you a chance to assess if Huntington is the right fit for you. Consider asking about the team dynamics, the tools and technologies they use, or how they measure success in the Data Engineering team. This will help you gain insights into the work environment and expectations.

Stay Calm and Professional

The interview process at Huntington is described as friendly and professional. Maintain a calm demeanor, and remember that the interviewers are interested in getting to know you as a person, not just your technical skills. Engage in the conversation, listen actively, and respond thoughtfully. This will help create a positive rapport with your interviewers and make the experience more enjoyable for both parties.

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

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Huntington National Bank. The interview process will likely focus on your technical skills, experience with data management, and your ability to work collaboratively within a team. Be prepared to discuss your past projects in detail, as interviewers will want to understand your thought process and the technologies you utilized.

Technical Skills

1. How would you implement polymorphic methods into a program structure?

This question assesses your understanding of object-oriented programming and design patterns.

How to Answer

Explain the concept of polymorphism and how it can be applied in your programming projects. Discuss specific scenarios where you have used polymorphic methods to enhance code reusability and maintainability.

Example

“In my previous project, I implemented polymorphic methods to create a flexible payment processing system. By defining a base class for payment methods and extending it for specific types like credit card and PayPal, I was able to streamline the payment process and easily add new payment options without modifying existing code.”

2. Can you describe your experience with cloud data solutions?

This question evaluates your familiarity with cloud technologies and your ability to implement data solutions in a cloud environment.

How to Answer

Discuss specific cloud platforms you have worked with, such as Azure or AWS, and detail the projects where you utilized these technologies. Highlight your role in designing and implementing cloud data architectures.

Example

“I have extensive experience with AWS, particularly in using S3 for data storage and Redshift for data warehousing. In a recent project, I migrated our on-premise data warehouse to AWS, which improved our data retrieval times by 40% and reduced costs significantly.”

3. What strategies do you use for data pipeline orchestration?

This question aims to understand your approach to managing data workflows and ensuring data quality.

How to Answer

Explain the tools and methodologies you use for orchestrating data pipelines, such as Apache Airflow or AWS Step Functions. Discuss how you ensure data integrity and reliability throughout the pipeline.

Example

“I typically use Apache Airflow for orchestrating data pipelines. I design workflows that include data validation steps to ensure data quality before it reaches the final destination. This approach has helped us reduce errors and improve the overall efficiency of our data processing.”

4. How do you ensure data quality in your projects?

This question assesses your understanding of data quality principles and practices.

How to Answer

Discuss the techniques you employ to maintain data quality, such as validation checks, data profiling, and automated testing. Provide examples of how you have implemented these practices in past projects.

Example

“In my last role, I implemented a data quality framework that included automated validation checks at each stage of the data pipeline. This not only helped us catch errors early but also provided stakeholders with confidence in the accuracy of our data.”

5. Describe a challenging data integration project you worked on. What were the key challenges and how did you overcome them?

This question evaluates your problem-solving skills and ability to handle complex data integration tasks.

How to Answer

Outline the project details, the challenges faced, and the solutions you implemented. Emphasize your role in the project and the impact of your contributions.

Example

“I worked on a project that involved integrating data from multiple legacy systems into a new data warehouse. The key challenge was dealing with inconsistent data formats. I developed a set of transformation scripts that standardized the data before loading it into the warehouse, which ultimately led to a successful integration and improved reporting capabilities.”

Teamwork and Culture Fit

1. How do you approach collaboration with cross-functional teams?

This question assesses your ability to work effectively with different teams and stakeholders.

How to Answer

Discuss your communication style and how you ensure alignment with other teams. Provide examples of successful collaborations in your past roles.

Example

“I believe in maintaining open lines of communication with cross-functional teams. In a recent project, I held regular check-ins with the analytics and business teams to ensure we were aligned on data requirements and project timelines. This proactive approach helped us avoid misunderstandings and deliver the project on time.”

2. Where do you see yourself in five years?

This question gauges your career aspirations and alignment with the company’s goals.

How to Answer

Share your professional goals and how they relate to the role you are applying for. Emphasize your desire for growth and contribution to the company.

Example

“In five years, I see myself in a leadership role within data engineering, where I can mentor junior engineers and lead innovative projects. I am excited about the opportunity to grow with Huntington and contribute to its data-driven initiatives.”

3. Why are you interested in accepting this role?

This question allows you to express your motivation for joining the company and the specific role.

How to Answer

Discuss what attracted you to the position and how it aligns with your skills and career goals. Mention any specific aspects of Huntington’s culture or mission that resonate with you.

Example

“I am drawn to this role because of Huntington’s commitment to innovation and teamwork. I believe my background in data engineering and my passion for building scalable data solutions align perfectly with the goals of your team. I am excited about the opportunity to contribute to impactful projects at Huntington.”

4. Why are you looking to leave your current position?

This question seeks to understand your motivations for seeking new opportunities.

How to Answer

Be honest but diplomatic. Focus on your desire for growth, new challenges, or a better fit rather than negative aspects of your current job.

Example

“I am looking to leave my current position because I am seeking new challenges that will allow me to grow my skills in data engineering. I am particularly excited about the opportunity at Huntington to work on innovative data solutions in a collaborative environment.”