Old National Bank has been serving clients and communities since 1834, establishing itself as a regional powerhouse committed to social responsibility and community investment.

As a Data Engineer at Old National Bank, you will be responsible for developing and implementing technical solutions that facilitate data exchange and integration for both internal and external stakeholders. This role requires a strong foundation in database applications and ETL processes, with a key focus on transitioning the bank to a modern data platform, including the integration of Salesforce and digital banking solutions. You will collaborate with cross-functional teams, utilize scripting tools such as Python, and work with Azure Databricks for enterprise data lakes. The ideal candidate will possess critical thinking and problem-solving skills, demonstrating the ability to work both independently and as part of a team. A strong technical passion for data engineering and a commitment to the bank's values of optimism, collaboration, inclusion, agility, and ethics will set you apart in this role.

This guide will help you prepare for your interview by providing insights into the expectations and competencies required for success at Old National Bank as a Data Engineer, allowing you to showcase your skills and alignment with the company's mission.

The interview process for the Data Engineer role at Old National Bank is structured to assess both technical skills and cultural fit within the organization. Here’s a detailed breakdown of the typical interview stages you can expect:

1. Initial Screening

The first step in the interview process is an initial screening, typically conducted by a recruiter. This conversation lasts about 30 minutes and focuses on your background, experience, and motivations for applying to Old National Bank. The recruiter will also provide insights into the company culture and the specifics of the Data Engineer role. This is an opportunity for you to express your interest in the position and ask any preliminary questions you may have.

2. Technical Assessment

Following the initial screening, candidates usually undergo a technical assessment. This may take place over a video call and involves a series of technical questions and problem-solving exercises. You can expect to discuss your experience with ETL processes, database applications, and automation tools. Be prepared to demonstrate your proficiency in scripting languages such as Python and your familiarity with Azure Databricks, as well as your understanding of data architecture principles.

3. Behavioral Interview

After the technical assessment, candidates typically participate in a behavioral interview. This round focuses on your past experiences and how they align with Old National Bank's core values, such as collaboration, inclusivity, and ethical practices. Interviewers will assess your ability to work independently and as part of a team, as well as your critical thinking and problem-solving skills. Expect to share specific examples from your previous roles that highlight your competencies in these areas.

4. Onsite Interview

The final stage of the interview process is an onsite interview, which may consist of multiple rounds with different team members, including data engineers and managers. Each session will last approximately 45 minutes and will cover both technical and behavioral aspects. You may be asked to present a case study or a project you have worked on, demonstrating your ability to design and implement data solutions. This is also a chance for you to engage with potential colleagues and get a feel for the team dynamics.

5. Final Review

After the onsite interviews, the hiring team will conduct a final review of all candidates. This may involve discussions about your fit within the team and the organization as a whole. If you are selected, you will receive an offer, which may include discussions about salary, benefits, and other employment terms.

As you prepare for your interview, consider the following questions that may arise during the process.

Here are some tips to help you excel in your interview for the Data Engineer role at Old National Bank.

Embrace the Company Culture

Old National Bank prides itself on its core values: optimism, collaboration, inclusivity, agility, and ethics. Familiarize yourself with these values and think about how your personal values align with them. During the interview, demonstrate your understanding of these principles through examples from your past experiences. Show that you are not just a technical fit but also a cultural fit for the organization.

Highlight Your Technical Expertise

Given the emphasis on modern data platforms and tools like Azure Databricks, ensure you are well-versed in the technologies mentioned in the job description. Be prepared to discuss your experience with ETL processes, data integration, and cloud-based architectures. Bring specific examples of projects where you successfully implemented these technologies, focusing on the impact your work had on the organization.

Showcase Problem-Solving Skills

Old National Bank values critical thinking and problem-solving abilities. Prepare to discuss challenges you have faced in previous roles and how you approached them. Use the STAR (Situation, Task, Action, Result) method to structure your responses, clearly outlining the problem, your thought process, the actions you took, and the outcomes. This will demonstrate your analytical skills and ability to develop effective solutions.

Communicate Effectively

Strong communication skills are essential, especially when presenting designs and solutions to senior leadership. Practice articulating complex technical concepts in a way that is accessible to non-technical stakeholders. Be ready to discuss how you have successfully collaborated with cross-functional teams in the past, emphasizing your ability to gather requirements and translate them into actionable data solutions.

Prepare for Behavioral Questions

Expect behavioral interview questions that assess your teamwork, leadership, and adaptability. Reflect on your past experiences and prepare examples that showcase your ability to work independently while also guiding and collaborating with team members. Highlight instances where you have fostered a culture of innovation or contributed to team success.

Understand the Role's Impact

Be prepared to discuss how the Data Engineer role contributes to the bank's overall mission of serving clients and communities. Research recent initiatives or projects at Old National Bank that align with your skills and experiences. This will not only show your interest in the role but also your understanding of how data engineering can drive business value.

Ask Insightful Questions

Prepare thoughtful questions to ask your interviewers that demonstrate your interest in the role and the company. Inquire about the team dynamics, ongoing projects, or how the bank is leveraging data to enhance customer experiences. This will show that you are proactive and genuinely interested in contributing to the organization.

Follow Up

After the interview, send a thank-you email to express your appreciation for the opportunity to interview. Reiterate your enthusiasm for the role and briefly mention a key point from the interview that reinforces your fit for the position. This will leave a positive impression and keep you top of mind as they make their decision.

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

Old National Bank Data Engineer Interview Questions

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Old National Bank. The interview will focus on your technical expertise in data engineering, including ETL processes, database applications, and cloud data platforms. Be prepared to demonstrate your problem-solving skills, ability to work with stakeholders, and your knowledge of modern data architectures.

Technical Skills

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

Understanding the ETL process is crucial for a Data Engineer, as it forms the backbone of data integration and transformation.

How to Answer

Discuss your experience with ETL processes, including the tools you used, the challenges you faced, and how you overcame them. Highlight specific projects where you successfully implemented ETL.

Example

“In my previous role, I designed an ETL pipeline using Azure Data Factory to extract data from various sources, transform it using Azure Databricks, and load it into our data warehouse. I faced challenges with data quality, which I addressed by implementing validation checks at each stage of the process.”

2. What is your experience with Azure Databricks, and how have you utilized it in your data engineering tasks?

Azure Databricks is a key tool for data engineers at Old National Bank, so familiarity with it is essential.

How to Answer

Share specific examples of how you have used Azure Databricks for data processing, including any challenges you faced and how you optimized performance.

Example

“I have used Azure Databricks extensively for processing large datasets. In one project, I optimized a data transformation job that initially took hours to run by leveraging Spark’s distributed computing capabilities, reducing the runtime to under 30 minutes.”

3. Describe your experience with T-SQL and how you have used it in your data engineering projects.

T-SQL is often used for querying and managing data in SQL Server, making it a vital skill for this role.

How to Answer

Discuss your proficiency with T-SQL, including complex queries, stored procedures, and performance tuning.

Example

“I have over five years of experience with T-SQL, where I developed complex stored procedures to automate data processing tasks. I also focused on query optimization, which improved the performance of our reporting queries by 40%.”

4. How do you ensure data quality and integrity in your data engineering processes?

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

How to Answer

Explain the methods you use to validate and clean data, as well as any tools or frameworks you have implemented to monitor data quality.

Example

“I implement data validation checks at various stages of the ETL process, using both automated scripts and manual reviews. Additionally, I set up monitoring dashboards to track data quality metrics, allowing us to quickly identify and address any issues.”

5. Can you discuss your experience with cloud-based data architectures?

As Old National Bank is moving towards modern data platforms, understanding cloud architectures is essential.

How to Answer

Share your experience with cloud services, particularly Azure, and how you have designed or implemented data solutions in the cloud.

Example

“I have designed cloud-based data architectures using Azure services, including Azure Data Lake and Azure Synapse Analytics. In a recent project, I migrated our on-premises data warehouse to Azure, which improved scalability and reduced costs significantly.”

Collaboration and Communication

1. Describe a time when you had to gather requirements from stakeholders for a data project. How did you approach it?

Collaboration with stakeholders is key in data engineering roles, and this question assesses your communication skills.

How to Answer

Discuss your approach to gathering requirements, including how you ensure clarity and alignment with stakeholders.

Example

“I organized a series of workshops with stakeholders to gather their requirements for a new reporting tool. I used visual aids to clarify complex concepts and ensured that everyone had a chance to voice their needs, which helped us create a solution that met all expectations.”

2. How do you communicate technical concepts to non-technical stakeholders?

Being able to bridge the gap between technical and non-technical teams is crucial in a banking environment.

How to Answer

Explain your strategies for simplifying complex technical information and ensuring understanding among non-technical audiences.

Example

“I often use analogies and visual representations to explain technical concepts. For instance, when discussing data flow, I compare it to a water pipeline, which helps non-technical stakeholders visualize how data moves through our systems.”

3. Can you provide an example of a successful project where you collaborated with other teams?

Collaboration is essential in data engineering, and this question assesses your teamwork skills.

How to Answer

Share a specific project where you worked with other teams, highlighting your role and the outcome of the collaboration.

Example

“I collaborated with the marketing team to develop a customer segmentation model. By working closely with them to understand their goals, we created a data-driven solution that improved targeted marketing efforts, resulting in a 20% increase in campaign effectiveness.”

4. How do you handle conflicts or disagreements with team members during a project?

Conflict resolution is an important skill in any collaborative environment.

How to Answer

Discuss your approach to resolving conflicts, emphasizing communication and compromise.

Example

“When conflicts arise, I prefer to address them directly by facilitating a discussion between the involved parties. I encourage open communication and focus on finding a solution that aligns with our project goals, which has helped maintain a positive team dynamic.”

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

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

How to Answer

Explain your methods for prioritizing tasks, including any tools or frameworks you use to manage your workload.

Example

“I use Agile methodologies to prioritize my tasks, breaking down projects into manageable sprints. I also maintain a Kanban board to visualize my workload, which helps me focus on high-impact tasks while ensuring that deadlines are met.”

• Write a function to merge two sorted lists into one sorted list. Given two sorted lists, write a function to merge them into one sorted list.

• Write a function to find the maximum number in a list of integers. Given a list of integers, write a function that returns the maximum number in the list. If the list is empty, return None.

• Write a query to get the top 3 highest employee salaries by department. Given the employees and departments table, write a query to get the top 3 highest employee salaries by department. If the department contains less than 3 employees, list the top 2 or top 1 highest salaries. The output should include the full name of the employee in one column, the department name, and the salary. The output should be sorted by department name in ascending order and salary in descending order.

• Write a function to combine sorted integer lists into one sorted list. Given a list of sorted integer lists, write a function sort_lists to create a combined list while maintaining sorted order without importing any libraries or using the 'sort' or 'sorted' functions in Python.

• Write a function to swap nodes in a singly linked list. Given the head of a singly linked list represented as a ListNode, and two zero-indexed positions x and y, write a function swap_node which swaps the positions of nodes x and y and returns the new head. Note that you cannot simply swap the values of these nodes; you must swap these two using pointer manipulation.

• How would you investigate a decrease in credit card payment amount per transaction? You work for a financial company and notice that the credit card payment amount per transaction has decreased. How would you investigate the cause of this change?

• How would you build a strategy to find the best small businesses to partner with? You are a credit card company looking to partner with more merchants. You have 100K small businesses to reach out to but can only contact 1000. How would you strategize to identify the best businesses to approach?

• What features would you include in a model to predict a no-show for pizza orders? Imagine you run a pizza franchise and face a problem with many no-shows after customers place their orders. What features would you include in a predictive model to address this issue?

• How does random forest generate the forest, and why use it over logistic regression? Explain the process by which a random forest generates its forest. Additionally, discuss why one might choose random forest over other algorithms such as logistic regression.

• How would you build a fraud detection model with a text messaging service for a bank? You work at a bank that wants to build a model to detect fraud on its platform. The bank also wants to implement a text messaging service that will text customers when the model detects a fraudulent transaction, allowing the customer to approve or deny the transaction via text. How would you build this model?

• What is the relationship between PCA and K-means clustering? Describe the relationship between Principal Component Analysis (PCA) and K-means clustering.

Interested in becoming part of a leading financial institution with a history dating back to 1834? At Old National Bank, we are dedicated to not only serving our clients but also investing in our communities and team members. The Data Engineer role offers a unique opportunity to contribute towards moving the bank to a modern data platform while collaborating with professionals passionate about innovation and excellence.

If you want more insights about the company, check out our Old National Bank Interview Guide, where we have covered many interview questions that could be asked. We’ve also created interview guides for other roles, such as software engineer and data analyst, where you can learn more about Old National Bank’s interview process for different positions.

At Interview Query, we empower you with a comprehensive toolkit, equipping you with the knowledge, confidence, and strategic guidance to conquer every interview challenge.

You can check out all our company interview guides for better preparation, and if you have any questions, don’t hesitate to reach out to us.

Good luck with your interview!