M&T Bank Data Engineer Interview Questions + Guide in 2025

M&T Bank is a prominent financial institution that focuses on delivering exceptional banking solutions and services to its customers while fostering a culture of teamwork and innovation.

As a Data Engineer at M&T Bank, you will play an essential role in developing and optimizing data pipelines and ETL processes within the enterprise data warehouse. Your key responsibilities will include building data pipelines for data ingestion and transformation using Snowflake, while ensuring efficient data migration from various sources. You will collaborate closely with cross-functional teams to maintain and enhance data integrity and availability, utilizing your strong SQL skills to write complex queries and manage data scheduling. Proficiency in Python and familiarity with cloud platforms such as Azure, AWS, or GCP will be crucial, as you will be expected to leverage internal frameworks and operate ETL processes on Linux servers. Additionally, experience in DevOps practices, particularly in CI/CD pipeline setup, will be advantageous.

A great fit for this role embodies a proactive approach to problem-solving, a keen eye for detail, and the ability to communicate effectively with both technical and non-technical stakeholders. Understanding data warehousing concepts and having hands-on experience with relevant technologies will further enhance your candidacy.

This guide will provide you with tailored insights and preparation strategies to help you excel in your interview for the Data Engineer position at M&T Bank.

The interview process for a Data Engineer at M&T Bank is structured to assess both technical and behavioral competencies, ensuring candidates are well-suited for the role and the company culture.

1. Initial HR Screening

The process typically begins with a phone interview conducted by an HR representative. This initial screening lasts about 30 minutes and focuses on your background, education, and general fit for the company. Expect questions about your interest in M&T Bank, your previous experiences, and your understanding of the role. This is also an opportunity for you to ask about the company culture and the specifics of the position.

2. Technical Interview

Following the HR screening, candidates usually participate in a technical interview. This round may be conducted via video call and typically lasts around 45 minutes to an hour. The focus here is on your technical skills, particularly in SQL, Python, and data engineering concepts. You may be asked to solve coding problems or discuss your experience with data pipelines, ETL processes, and cloud technologies like Azure, AWS, or GCP. Be prepared to demonstrate your knowledge of Snowflake and your ability to write complex SQL queries.

3. Team Interviews

Candidates who perform well in the technical interview will often move on to meet with team members. This stage may consist of multiple interviews with different team members, including senior engineers and managers. These interviews are designed to assess your collaborative skills and how well you would fit within the team. Expect a mix of behavioral questions and discussions about your past projects, particularly those involving data migration and ETL development.

4. Final Interview

The final round typically involves a more in-depth discussion with higher-level management or executives. This interview may cover your long-term career goals, your approach to problem-solving, and how you handle challenges in a team setting. It’s also an opportunity for you to showcase your leadership qualities and discuss how your technical skills align with the company’s objectives.

5. Reference Check

After successfully completing the interviews, candidates may undergo a reference check. This step is crucial as M&T Bank values the insights from previous employers regarding your work ethic and technical capabilities.

As you prepare for your interviews, consider the types of questions that may arise in each of these stages, particularly those that relate to your technical expertise and past experiences.

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

Understand the Role and Company Culture

Before your interview, take the time to thoroughly understand the role of a Data Engineer at M&T Bank. Familiarize yourself with the specific technologies mentioned in the job description, such as Snowflake, SQL, and Python. Additionally, research M&T Bank's values and culture. The company emphasizes collaboration and a friendly work environment, so be prepared to discuss how you can contribute positively to the team dynamic.

Prepare for Behavioral Questions

Expect a mix of behavioral and technical questions during your interviews. M&T Bank interviewers often focus on how your past experiences align with the role. Use the STAR (Situation, Task, Action, Result) method to structure your responses. Be ready to share specific examples of how you've handled challenges, collaborated with team members, or contributed to successful projects in your previous roles.

Brush Up on Technical Skills

Given the emphasis on SQL and data engineering tools, ensure you are well-versed in writing complex SQL queries and have a solid understanding of data warehousing concepts. Practice coding challenges that involve data manipulation and transformation, as well as any relevant ETL processes. Familiarize yourself with Snowflake and its functionalities, as well as the cloud platforms mentioned in the job description (Azure, AWS, GCP).

Showcase Your Problem-Solving Abilities

During technical interviews, you may be asked to solve problems on the spot. Be prepared to demonstrate your thought process clearly and logically. Interviewers at M&T Bank appreciate candidates who can articulate their reasoning and approach to problem-solving. If you encounter a challenging question, don't hesitate to ask clarifying questions or think aloud to show your analytical skills.

Communicate Your Interest in the Company

M&T Bank values candidates who show genuine interest in the organization and the financial industry. Be prepared to discuss why you want to work at M&T Bank specifically and how your skills align with their mission. This can help you stand out as a candidate who is not only qualified but also enthusiastic about contributing to the company's success.

Be Ready for a Lengthy Process

The interview process at M&T Bank can be extensive, often involving multiple rounds with different team members. Stay patient and maintain a positive attitude throughout the process. Use this time to ask insightful questions about the team, projects, and company culture, which can further demonstrate your interest and engagement.

Follow Up Thoughtfully

After your interviews, send a thoughtful thank-you email to your interviewers. Express your appreciation for the opportunity to learn more about the team and the role. This not only reinforces your interest but also leaves a positive impression.

By following these tips and preparing thoroughly, you can position yourself as a strong candidate for the Data Engineer role at M&T Bank. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at M&T Bank. The interview process will likely assess both technical skills and behavioral competencies, focusing on your experience with data engineering, SQL, ETL processes, and your ability to work collaboratively within a team.

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 involves extracting, transforming, and loading data into a data warehouse.

How to Answer

Discuss your experience with ETL tools and frameworks, emphasizing specific projects where you successfully implemented ETL processes. Highlight any challenges you faced and how you overcame them.

Example

“In my previous role, I developed an ETL pipeline using Apache NiFi to extract data from various sources, transform it using Python scripts, and load it into our Snowflake data warehouse. One challenge was ensuring data quality, which I addressed by implementing validation checks at each stage of the process.”

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

SQL proficiency is essential for data manipulation and querying in data engineering roles.

How to Answer

Provide a brief overview of your SQL experience, then describe a specific complex query you wrote, explaining its purpose and the outcome.

Example

“I have over five years of experience with SQL, primarily in data extraction and reporting. For instance, I wrote a complex query that involved multiple joins and subqueries to generate a comprehensive sales report, which helped the management team identify trends and make informed decisions.”

3. Describe your experience with Snowflake and how you have utilized it in your projects.

Snowflake is a key technology for data warehousing, and familiarity with it is often required.

How to Answer

Discuss your hands-on experience with Snowflake, including any specific features you have used and how they benefited your projects.

Example

“I have worked extensively with Snowflake for data warehousing solutions. I utilized its capabilities for data sharing and scaling, which allowed us to handle large datasets efficiently. In one project, I set up a Snowflake instance that reduced our query times by 30% compared to our previous solution.”

4. How do you approach data migration from one system to another?

Data migration is a common task for Data Engineers, and understanding the best practices is important.

How to Answer

Explain your methodology for data migration, including planning, execution, and validation steps.

Example

“When migrating data, I first conduct a thorough analysis of the source and target systems to understand the data structure. I then create a detailed migration plan, execute the migration using ETL tools, and finally validate the data integrity by comparing sample records from both systems.”

5. Can you explain the concept of data warehousing and its importance?

A solid understanding of data warehousing concepts is essential for a Data Engineer.

How to Answer

Define data warehousing and discuss its significance in data management and analytics.

Example

“Data warehousing is the process of collecting and managing data from various sources to provide meaningful business insights. It is crucial because it allows organizations to consolidate data, perform complex queries, and generate reports that inform strategic decisions.”

Behavioral Questions

1. Describe a challenging project you worked on and how you handled it.

This question assesses your problem-solving skills and resilience.

How to Answer

Choose a specific project, describe the challenge, and explain the steps you took to resolve it.

Example

“I worked on a project where we had to integrate data from multiple legacy systems into a new data warehouse. The challenge was the inconsistent data formats. I led a team to standardize the data formats and implemented a robust validation process, which ultimately led to a successful migration.”

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

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

How to Answer

Discuss your approach to prioritizing tasks, including any tools or methods you use.

Example

“I prioritize tasks based on project deadlines and the impact on business operations. I use project management tools like Jira to track progress and ensure that I am focusing on high-impact tasks first. Regular communication with my team also helps in aligning priorities.”

3. Can you give an example of how you have collaborated with team members on a project?

Collaboration is essential in a team environment, especially in data engineering.

How to Answer

Share a specific example of a project where teamwork was crucial, highlighting your role and contributions.

Example

“In a recent project, I collaborated with data analysts and software engineers to develop a new reporting tool. I facilitated regular meetings to ensure everyone was aligned on the project goals and shared updates on our progress. This collaboration led to a successful launch of the tool ahead of schedule.”

4. How do you handle feedback and criticism from peers or supervisors?

This question evaluates your ability to accept feedback and grow from it.

How to Answer

Discuss your perspective on feedback and provide an example of how you have used it constructively.

Example

“I view feedback as an opportunity for growth. For instance, after receiving feedback on my data visualization skills, I took an online course to improve. This not only enhanced my skills but also allowed me to contribute more effectively to team projects.”

5. Why do you want to work at M&T Bank, and what do you hope to contribute?

Understanding your motivation for applying and your potential contributions is important for the interviewers.

How to Answer

Express your interest in the company and how your skills align with their goals.

Example

“I am drawn to M&T Bank because of its commitment to innovation and customer service. I believe my experience in building efficient data pipelines and my passion for data-driven decision-making will allow me to contribute significantly to your data engineering team.”