The Huntington Software Engineer Interview Guide

Getting ready for a Software Engineer interview at The Huntington? The Huntington Software Engineer interview process typically spans multiple question topics and evaluates skills in areas like software architecture, coding, debugging, system design, and collaborative problem-solving. Interview preparation is especially important for this role at The Huntington, as candidates are expected to demonstrate their ability to design, develop, and support robust applications within an Agile environment, while also showcasing their experience with modern front-end frameworks, DevOps practices, and cloud-based solutions.

In preparing for the interview, you should:

• Understand the core skills necessary for Software Engineer positions at The Huntington.
• Gain insights into The Huntington’s Software Engineer interview structure and process.
• Practice real The Huntington Software Engineer interview questions to sharpen your performance.

At Interview Query, we regularly analyze interview experience data shared by candidates. This guide uses that data to provide an overview of the The Huntington Software Engineer interview process, along with sample questions and preparation tips tailored to help you succeed.

The Huntington National Bank is a leading regional bank headquartered in Columbus, Ohio, serving individuals, small businesses, and commercial clients across the Midwest and beyond. With a focus on customer-centric financial services, Huntington provides a wide range of offerings, including personal and business banking, lending, wealth management, and digital banking solutions. The company emphasizes innovation, integrity, and community engagement as core values. As a Software Engineer, you will contribute to the development and support of digital applications that drive Huntington’s commercial banking operations, playing a key role in enhancing customer experience and supporting the bank’s digital transformation initiatives.

As a Software Engineer at The Huntington, you will design, develop, integrate, and support applications for the Commercial Digital business segment, often taking a lead role among developers. You’ll collaborate closely with other developers and architects to build and review frontend components, participate in Agile ceremonies, and contribute to technical design discussions. Your responsibilities include supporting production releases, resolving incident tickets, performing code reviews, and ensuring integration testing. You will work in a fast-paced, collaborative environment, leveraging modern technologies such as ReactJS, Java, and cloud platforms, and contribute to continuous improvement through DevOps practices. This role is key to delivering reliable, high-quality digital solutions that support The Huntington’s commercial operations.

2.1 Stage 1: Application & Resume Review

The process begins with a thorough review of your application and resume by the Huntington recruiting team. They look for evidence of strong front-end development skills (HTML, CSS, JavaScript, ReactJS, TypeScript), experience with modern software engineering practices (Agile, DevOps, CI/CD), and familiarity with code repositories and testing frameworks. Highlight your experience with cloud solutions (AWS, GCP), API integration, and collaborative development environments. To prepare, ensure your resume clearly details your technical expertise, leadership in Agile teams, and contributions to production releases and incident resolution.

2.2 Stage 2: Recruiter Screen

Next, a recruiter will contact you for a preliminary phone screen, typically lasting 30 minutes. This conversation focuses on your background, motivation for joining Huntington, and alignment with the company’s collaborative culture. You should be ready to discuss your previous projects, your approach to learning new technologies, and your experience working in fast-paced environments. Preparation involves articulating your career narrative, emphasizing adaptability, and demonstrating your interest in Huntington’s digital initiatives.

2.3 Stage 3: Technical/Case/Skills Round

This round is conducted by technical team members and may include both conceptual questions and live coding challenges, often on a Coderpad-style platform. Expect to demonstrate your proficiency in front-end frameworks (especially ReactJS), Java development (Spring Framework, Maven/Gradle), and automated testing (Jest, Playwright). You may also be asked to solve algorithmic problems, design system components, and discuss approaches to debugging or production incident resolution. Prepare by reviewing relevant technologies, practicing coding in a collaborative environment, and being ready to explain your design decisions and testing methodologies.

2.4 Stage 4: Behavioral Interview

A behavioral interview, sometimes combined with technical questions, is typically conducted by a hiring manager or team lead. This stage explores your teamwork, leadership, and problem-solving skills in the context of Agile development, code reviews, and production support. You will need to provide examples of how you handle multi-tasking, collaborate with cross-functional teams, and contribute to continuous integration and deployment. Preparation should focus on specific stories from your experience that showcase initiative, tenacity, and your ability to thrive in a collaborative setting.

2.5 Stage 5: Final/Onsite Round

The final round often includes a panel or multiple interviews with technical leads, architects, and possibly product managers. These sessions dive deeper into your technical expertise, ability to lead other developers, and fit within Huntington’s engineering culture. You may be asked to participate in case studies, system design exercises, and provide insights into Agile ceremonies and production releases. Preparation is key—review how you’ve contributed to software delivery, managed production incidents, and driven process improvements.

2.6 Stage 6: Offer & Negotiation

If successful, you’ll receive an offer and enter the negotiation phase with Huntington’s recruiting team. This is your opportunity to discuss compensation, benefits, workplace flexibility, and any specific questions about team structure or career growth. Be prepared to address your compensation expectations and clarify any details about Huntington’s hybrid work model.

2.7 Average Timeline

The average Huntington Software Engineer interview process spans 2 to 4 weeks from application to offer. Fast-track candidates may complete the process in under two weeks, while standard pacing allows for scheduling flexibility and multiple rounds. The technical and behavioral interviews are typically scheduled within a week of the initial recruiter screen, and onsite rounds may be consolidated into a single day or split across several sessions depending on team availability.

Now, let’s dive into the types of interview questions you can expect at each stage.

3.1. System Design & Architecture

Expect questions that probe your understanding of scalable system design, data modeling, and performance optimization. Focus on demonstrating your ability to break down requirements, architect robust solutions, and communicate trade-offs clearly.

3.1.1 System design for a digital classroom service
Clarify user roles, major features, and data flows. Discuss database choices, scalability strategies, and how you’d address security and privacy for sensitive educational data.

3.1.2 Design a data warehouse for a new online retailer
Outline your approach to schema design, ETL pipelines, and how you’d ensure efficient querying and reporting for various business stakeholders.

3.1.3 Migrating a social network's data from a document database to a relational database for better data metrics
Discuss challenges in schema mapping, data consistency, and migration planning. Explain how you’d minimize downtime and validate data integrity post-migration.

3.1.4 Designing a secure and user-friendly facial recognition system for employee management while prioritizing privacy and ethical considerations
Highlight authentication flows, data encryption, and privacy safeguards. Address regulatory compliance and how you’d structure the system to minimize risk.

3.2. Algorithms & Data Structures

These questions assess your ability to solve complex problems efficiently and write maintainable code. Emphasize your thought process, optimal solutions, and edge case handling.

3.2.1 Create your own algorithm for the popular children's game, "Tower of Hanoi"
Break down the recursive solution, explain the base case, and discuss how you’d optimize for larger input sizes.

3.2.2 The task is to implement a shortest path algorithm (like Dijkstra's or Bellman-Ford) to find the shortest path from a start node to an end node in a given graph. The graph is represented as a 2D array where each cell represents a node and the value in the cell represents the cost to traverse to that node.
Clarify your choice of algorithm, discuss time and space complexity, and show how you handle cycles or unreachable nodes.

3.2.3 Implement Dijkstra's shortest path algorithm for a given graph with a known source node.
Explain your implementation steps, how you manage priority queues, and how you’d extend the solution to handle weighted and unweighted graphs.

3.2.4 Write a function to return the value of the nearest node that is a parent to both nodes.
Describe your approach for traversing binary trees, handling edge cases, and optimizing for time complexity.

3.3. Machine Learning & Modeling

You’ll be evaluated on your understanding of data-driven modeling, feature engineering, and model evaluation. Be ready to discuss both theory and practical implementation.

3.3.1 Building a model to predict if a driver on Uber will accept a ride request or not
Discuss feature selection, data preprocessing, and evaluation metrics. Explain how you’d handle imbalanced data and real-time prediction constraints.

3.3.2 Identify requirements for a machine learning model that predicts subway transit
Outline data sources, feature engineering, and model selection. Address scalability and latency concerns for real-world deployment.

3.3.3 Explaining the use/s of LDA related to machine learning
Describe the intuition behind LDA, its applications in classification, and how you’d explain its benefits to non-technical stakeholders.

3.3.4 Explain Neural Nets to Kids
Use simple analogies to convey the concept, focusing on layers, learning, and how neural networks “recognize” patterns.

3.3.5 Backpropagation Explanation
Summarize the mathematical intuition, how gradients are calculated, and why backpropagation is critical for deep learning models.

3.4. Data Analysis & Quality

These questions test your ability to analyze, clean, and interpret data for actionable insights. Demonstrate your rigor in handling messy datasets and your communication skills with non-technical audiences.

3.4.1 Describing a real-world data cleaning and organization project
Walk through your process for identifying issues, choosing cleaning strategies, and validating results. Emphasize reproducibility and documentation.

3.4.2 How would you approach improving the quality of airline data?
Discuss profiling, root cause analysis, and automated data validation checks. Show how you prioritize fixes for business impact.

3.4.3 Demystifying data for non-technical users through visualization and clear communication
Explain how you tailor visualizations, use storytelling, and bridge the gap between technical analysis and business decisions.

3.4.4 How to present complex data insights with clarity and adaptability tailored to a specific audience
Describe your approach to structuring presentations, using visual aids, and adapting depth for different stakeholders.

3.5. Product & Business Impact

Expect questions about how your work drives business outcomes, aligns with strategy, and communicates value across teams. Focus on metrics, experimentation, and stakeholder engagement.

3.5.1 How would you analyze how the feature is performing?
Describe the key metrics you’d track, how you’d set up A/B tests, and interpret results for actionable recommendations.

3.5.2 Let's say that we want to improve the "search" feature on the Facebook app.
Break down user needs, propose measurable improvements, and discuss how you’d validate success post-launch.

3.5.3 Assessing the market potential and then use A/B testing to measure its effectiveness against user behavior
Explain your approach to experimentation, success metrics, and communicating findings to product leadership.

3.5.4 How would you evaluate whether a 50% rider discount promotion is a good or bad idea? How would you implement it? What metrics would you track?
Discuss experimental design, key business KPIs, and how you’d assess short- and long-term impacts.

3.6 Behavioral Questions

3.6.1 Tell me about a time you used data to make a decision.
Focus on describing the business context, the analysis you performed, and the impact your recommendation had. Example: "While working on a payments feature, I analyzed transaction data to identify a bottleneck, recommended a UI change, and saw conversion rates increase by 15%."

3.6.2 Describe a challenging data project and how you handled it.
Highlight the obstacles, your problem-solving approach, and how you collaborated with others to reach a successful outcome. Example: "I led a migration from legacy systems, overcoming data inconsistencies by building validation scripts and aligning cross-team priorities."

3.6.3 How do you handle unclear requirements or ambiguity?
Show your proactive communication, iterative scoping, and how you validate assumptions with stakeholders. Example: "When project specs were vague, I scheduled stakeholder interviews and prototyped early solutions to clarify needs."

3.6.4 Talk about a time when you had trouble communicating with stakeholders. How were you able to overcome it?
Emphasize your adaptability, use of visualizations, and feedback loops. Example: "I realized my technical jargon was confusing, so I switched to annotated dashboards and regular check-ins to ensure alignment."

3.6.5 Describe a situation where two source systems reported different values for the same metric. How did you decide which one to trust?
Discuss your approach to data validation, root cause analysis, and collaboration with engineering or business teams. Example: "I traced data lineage, compared logs, and collaborated with both teams to reconcile discrepancies and standardize the metric."

3.6.6 Tell me about a time you delivered critical insights even though 30% of the dataset had nulls. What analytical trade-offs did you make?
Show your understanding of missing data patterns, chosen imputation or exclusion methods, and how you communicated uncertainty. Example: "I profiled missingness, used model-based imputation, and included confidence intervals in my report."

3.6.7 Describe a time you had to negotiate scope creep when two departments kept adding 'just one more' request. How did you keep the project on track?
Highlight your prioritization framework, transparent communication, and how you protected data quality. Example: "I used MoSCoW prioritization, quantified impacts, and secured leadership sign-off to maintain project scope."

3.6.8 Give an example of automating recurrent data-quality checks so the same dirty-data crisis doesn’t happen again.
Focus on your initiative, technical solution, and the long-term impact. Example: "I built automated scripts for data validation, reducing manual effort by 80% and improving reliability for downstream analytics."

3.6.9 Tell me about a situation where you had to influence stakeholders without formal authority to adopt a data-driven recommendation.
Show your persuasion skills, use of prototypes, and how you built consensus. Example: "I created wireframes to illustrate the benefits of my approach, shared pilot results, and convinced leadership to invest in the new analytics tool."

3.6.10 Describe how you prioritized backlog items when multiple executives marked their requests as 'high priority.'
Discuss your criteria for prioritization, communication strategy, and stakeholder management. Example: "I evaluated business impact, technical feasibility, and communicated trade-offs transparently to align on a shared roadmap."

4.1 Company-specific tips:

Immerse yourself in The Huntington’s core values—innovation, integrity, and customer-centricity. Review their digital banking initiatives and how technology is transforming financial services for both commercial and individual clients. Be prepared to discuss how software engineering can drive improvements in customer experience, security, and operational efficiency within a banking context.

Demonstrate your understanding of regulatory requirements and security standards relevant to financial institutions. Highlight your awareness of privacy, compliance, and risk management, and be ready to explain how you would build secure, compliant applications for banking customers.

Research Huntington’s recent technology investments, such as cloud adoption, Agile transformation, and digital product launches. Show enthusiasm for contributing to their ongoing digital transformation and bring ideas for how technology can help Huntington innovate in the competitive Midwest banking landscape.

4.2 Role-specific tips:

4.2.1 Show expertise in front-end frameworks, especially ReactJS, and modern Java development.
Review your experience with HTML, CSS, JavaScript, and TypeScript, focusing on how you build scalable, maintainable user interfaces. Be ready to discuss your approach to component design, state management, and integration with backend APIs using ReactJS. For backend, demonstrate your proficiency with Java, Spring Framework, and build tools like Maven or Gradle, emphasizing how you design robust, modular services.

4.2.2 Practice system design and architecture with a focus on scalability, reliability, and security.
Prepare to break down requirements for banking applications, design secure data flows, and discuss trade-offs in technology choices. Explain how you would architect solutions to handle sensitive financial data, ensure high availability, and support future growth. Use examples from past projects to illustrate your decision-making process and technical leadership.

4.2.3 Be ready to solve live coding challenges and discuss your debugging strategies.
Sharpen your skills in algorithms, data structures, and problem-solving. Practice writing clean, efficient code and narrate your thought process as you work through problems. Be prepared to explain how you identify and resolve bugs, optimize for performance, and write tests to validate your solutions.

4.2.4 Highlight your experience with Agile, DevOps, and CI/CD practices.
Describe your role in Agile ceremonies, sprint planning, and collaborative development. Discuss how you use CI/CD pipelines to automate builds, tests, and deployments, and how you contribute to continuous improvement. Provide examples of how you’ve supported production releases, handled incident tickets, and improved deployment reliability.

4.2.5 Prepare stories that showcase your teamwork, leadership, and ability to deliver under pressure.
Reflect on times you’ve led code reviews, mentored junior engineers, or resolved conflicts within a development team. Be ready to share how you prioritize tasks, communicate with cross-functional stakeholders, and maintain quality while meeting tight deadlines. Use the STAR method (Situation, Task, Action, Result) to structure your responses for behavioral questions.

4.2.6 Demonstrate your ability to learn new technologies and adapt to fast-paced environments.
Share examples of how you’ve quickly ramped up on unfamiliar frameworks, tools, or business domains. Highlight your curiosity, resourcefulness, and commitment to continuous learning—qualities that are highly valued at The Huntington.

4.2.7 Articulate your approach to building secure, user-friendly applications for financial services.
Discuss how you balance usability with security, especially in authentication, data encryption, and regulatory compliance. Explain how you would design features to protect customer data, prevent fraud, and comply with industry standards.

4.2.8 Prepare to discuss business impact and how your engineering work drives measurable outcomes.
Show that you understand how to track feature performance, set up experiments, and communicate results to stakeholders. Be ready to explain how your technical decisions support Huntington’s strategic goals and improve customer satisfaction.

4.2.9 Be thoughtful about how you communicate complex technical concepts to non-technical audiences.
Practice explaining your design decisions, project outcomes, and technical challenges in clear, accessible language. Use visual aids, analogies, or storytelling to bridge the gap between engineering and business stakeholders.

4.2.10 Bring examples of how you’ve handled ambiguous requirements, scope changes, and competing priorities.
Share your strategies for clarifying project goals, managing expectations, and keeping projects on track despite evolving needs. Emphasize your proactive communication and ability to adapt while maintaining focus on quality and delivery.

5.1 “How hard is the The Huntington Software Engineer interview?”
The Huntington Software Engineer interview is considered moderately challenging, especially for those with a strong foundation in both front-end and back-end development. The process tests your skills in coding, system design, debugging, and Agile collaboration, with an emphasis on real-world problem-solving and the ability to build secure, scalable applications for the financial sector. Candidates who are well-prepared in modern frameworks, DevOps practices, and cloud technologies tend to perform best.

5.2 “How many interview rounds does The Huntington have for Software Engineer?”
You can expect 4 to 5 rounds in the Huntington Software Engineer interview process. These typically include an initial recruiter screen, a technical/coding round, a behavioral interview, and a final onsite or virtual panel round with technical leads and hiring managers. Some candidates may also encounter a take-home assignment or technical case study depending on the team.

5.3 “Does The Huntington ask for take-home assignments for Software Engineer?”
While not always required, some teams at The Huntington may include a take-home coding or technical design assignment as part of the process. These assignments are designed to assess your practical coding skills, architectural thinking, and ability to solve problems independently. Be prepared to clearly document your approach and reasoning if given such an assignment.

5.4 “What skills are required for the The Huntington Software Engineer?”
Key skills include proficiency in front-end frameworks (especially ReactJS), Java development (Spring Framework, Maven/Gradle), HTML, CSS, JavaScript, TypeScript, and experience with cloud platforms like AWS or GCP. Familiarity with Agile methodologies, DevOps practices, CI/CD pipelines, and automated testing is highly valued. Strong communication, teamwork, and the ability to design secure, user-friendly applications are essential for success in this role.

5.5 “How long does the The Huntington Software Engineer hiring process take?”
The typical hiring process at The Huntington spans 2 to 4 weeks from application to offer. Fast-track candidates may move through the process in less than two weeks, while others may experience a slightly longer timeline depending on scheduling and team availability. The process is designed to be thorough, ensuring both technical and cultural fit.

5.6 “What types of questions are asked in the The Huntington Software Engineer interview?”
You’ll encounter a mix of technical and behavioral questions. Technical questions cover system design, architecture, coding challenges (often in Java or JavaScript), debugging, and DevOps practices. Expect scenario-based questions about building secure banking applications, optimizing for scalability, and integrating with APIs. Behavioral questions focus on teamwork, leadership, communication, and your experience working in Agile environments.

5.7 “Does The Huntington give feedback after the Software Engineer interview?”
The Huntington typically provides feedback through their recruiting team. While detailed technical feedback may be limited, you can expect to receive high-level insights on your interview performance and areas for improvement, especially if you reach the later rounds.

5.8 “What is the acceptance rate for The Huntington Software Engineer applicants?”
While specific acceptance rates are not publicly disclosed, the Software Engineer role at The Huntington is competitive. The estimated acceptance rate is around 3-5% for qualified applicants, reflecting the company’s high standards and focus on finding candidates who align with both technical requirements and company values.

5.9 “Does The Huntington hire remote Software Engineer positions?”
Yes, The Huntington offers hybrid and some fully remote Software Engineer positions, depending on team needs and project requirements. Many roles provide flexibility with remote work, though certain teams may require periodic onsite collaboration for key meetings or project milestones. Be sure to clarify expectations with your recruiter during the interview process.

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Ready to ace your The Huntington Software Engineer interview? It’s not just about knowing the technical skills—you need to think like a The Huntington Software Engineer, solve problems under pressure, and connect your expertise to real business impact. That’s where Interview Query comes in with company-specific learning paths, mock interviews, and curated question banks tailored toward roles at The Huntington and similar companies.

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