AvidXchange Data Engineer Interview Questions + Guide in 2025

AvidXchange is a leading provider of accounts payable automation software and payment solutions, dedicated to empowering middle-market businesses and their suppliers through innovative technology.

As a Data Engineer, you will be instrumental in constructing and optimizing robust data solutions that enhance data ingestion, quality, and management, with a particular emphasis on Master Data Management (MDM). This role requires collaboration with Principal Engineers, Solution Architects, and Product Managers to create scalable and modern data systems that align with AvidXchange’s commitment to customer-centric innovation. Success in this position hinges on a strong foundation in data engineering principles, API development, and event-driven architectures, alongside a proactive, growth-oriented mindset that resonates with the company’s culture of connection and continuous improvement. The ideal candidate will possess both the technical acumen to implement advanced data solutions and the soft skills necessary to foster cross-functional collaboration.

This guide is designed to equip you with the insights and strategies needed to excel in your upcoming interview, ensuring you present yourself as a well-rounded candidate aligned with AvidXchange's core values and mission.

The interview process for a Data Engineer at AvidXchange is structured to assess both technical expertise and cultural fit within the organization. Typically, the process unfolds over a span of two weeks and consists of multiple stages designed to evaluate your skills and experiences comprehensively.

1. Initial Phone Interview

The first step in the interview process is a phone interview with a recruiter. This conversation usually lasts about 30 to 60 minutes and serves as an opportunity for the recruiter to gauge your interest in the role and the company. During this call, you will discuss your background, relevant experiences, and motivations for applying to AvidXchange. The recruiter will also provide insights into the company culture and the expectations for the Data Engineer role.

2. Technical Interview

If you successfully pass the initial screening, you will be invited to a technical interview. This stage may take place over video conferencing or in person, depending on the circumstances. The technical interview typically lasts around an hour and focuses on your proficiency in data engineering concepts, algorithms, and data structures. Expect to encounter questions that assess your understanding of data ingestion, data quality, and Master Data Management (MDM) principles. You may also be asked to solve coding problems or discuss your previous projects in detail.

3. Onsite Interview

The final stage of the interview process is the onsite interview, which can last several hours and consists of multiple rounds. During this phase, you will meet with various team members, including hiring managers and other data engineers. The onsite interviews are divided into technical and behavioral segments. The technical rounds will delve deeper into your expertise in building data pipelines, API development, and event-driven architectures. The behavioral interviews will assess your soft skills, teamwork, and alignment with AvidXchange's core values, such as being customer-obsessed and growth-minded.

Throughout the interview process, candidates are encouraged to demonstrate their problem-solving abilities, analytical skills, and collaborative mindset, as these traits are highly valued at AvidXchange.

As you prepare for your interviews, it’s essential to familiarize yourself with the types of questions that may be asked during each stage.

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

Understand the Interview Structure

AvidXchange typically follows a two-stage interview process. The first stage is often a phone interview, which serves as a preliminary screening. The second stage usually involves an onsite interview that includes both behavioral and technical components. Familiarize yourself with this structure so you can prepare accordingly. Expect to discuss your past experiences and how they relate to the role, as well as technical questions that assess your knowledge of data engineering principles.

Prepare for Technical Questions

Given the emphasis on technical skills in the role, be ready to dive deep into topics such as algorithms, data structures, and data quality principles. Brush up on your knowledge of APIs, event streaming architectures, and Master Data Management (MDM) solutions. You may encounter questions specifically about Hashmaps and data ingestion frameworks, so practice coding problems and be prepared to explain your thought process clearly.

Showcase Your Collaboration Skills

AvidXchange values teamwork and collaboration, as the role requires working closely with Principal Engineers, Solution Architects, and Product Managers. Be prepared to discuss examples of how you have successfully collaborated with cross-functional teams in the past. Highlight your ability to communicate effectively with both technical and non-technical stakeholders, as this will demonstrate your fit within the company culture.

Emphasize Your Growth Mindset

AvidXchange prides itself on a culture that is "Growth Minded." During your interview, convey your willingness to learn and adapt. Share experiences where you took initiative to improve your skills or processes, and express your enthusiasm for staying updated with emerging technologies in data engineering. This will resonate well with the company's values and show that you align with their mission.

Align with Company Values

Familiarize yourself with AvidXchange's core values: being connected as people, being customer-obsessed, and having a growth mindset. During the interview, weave these values into your responses. For instance, when discussing your past work, relate how your actions contributed to customer satisfaction or how you fostered connections within your team. This alignment will help you stand out as a candidate who truly understands and embodies the company culture.

Prepare Thoughtful Questions

At the end of the interview, you will likely have the opportunity to ask questions. Use this time to demonstrate your interest in the role and the company. Ask about the team dynamics, ongoing projects, or how AvidXchange measures success in data engineering. Thoughtful questions not only show your engagement but also help you assess if the company is the right fit for you.

Follow Up Professionally

After your interview, send a thank-you email to express your appreciation for the opportunity to interview. Reiterate your interest in the role and briefly mention a key point from your conversation that resonated with you. This not only shows professionalism but also keeps 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 AvidXchange. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at AvidXchange. The interview process will likely focus on your technical expertise in data engineering, your understanding of Master Data Management (MDM), and your ability to collaborate with cross-functional teams. Be prepared to demonstrate your problem-solving skills and your knowledge of modern data practices.

Technical Skills

1. Can you explain the differences between batch processing and real-time processing?

Understanding the distinctions between these two processing types is crucial for a Data Engineer, especially in a role that involves building scalable data pipelines.

How to Answer

Discuss the characteristics of both processing types, including their use cases, advantages, and disadvantages. Highlight scenarios where each would be appropriate.

Example

"Batch processing involves collecting data over a period and processing it all at once, which is efficient for large volumes of data but may not provide real-time insights. In contrast, real-time processing allows for immediate data processing, which is essential for applications requiring instant feedback, such as fraud detection systems."

2. Describe your experience with Master Data Management (MDM) solutions.

MDM is a key responsibility in this role, and interviewers will want to know your familiarity with MDM principles and tools.

How to Answer

Share specific examples of MDM projects you've worked on, the tools you used, and the outcomes of those projects.

Example

"I have implemented MDM solutions using Reltio, where I focused on ensuring data accuracy and integrity across various business units. This involved designing data models and automating data quality checks, which significantly reduced discrepancies in our customer data."

3. What strategies do you use to ensure data quality in your pipelines?

Data quality is paramount in data engineering, and interviewers will assess your approach to maintaining it.

How to Answer

Discuss the methods you employ for data validation, monitoring, and error handling in your data pipelines.

Example

"I implement automated validation checks at various stages of the data pipeline to catch anomalies early. Additionally, I use monitoring tools to track data quality metrics and set up alerts for any discrepancies, allowing for quick remediation."

4. Can you explain how you would design a data ingestion framework?

This question tests your ability to architect data solutions that are scalable and efficient.

How to Answer

Outline the key components of a data ingestion framework, including data sources, processing methods, and storage solutions.

Example

"I would design a data ingestion framework that utilizes event-driven architecture, leveraging tools like Azure Event Hubs for real-time data capture. The framework would include data transformation processes to ensure compatibility with our data warehouse, and I would implement robust logging for monitoring data flow."

5. What is your experience with API development for data access?

APIs are essential for data integration, and your experience in this area will be evaluated.

How to Answer

Discuss your experience in designing and implementing APIs, including the technologies you used and the challenges you faced.

Example

"I have developed RESTful APIs using Python and Flask to facilitate data access for various applications. One challenge I faced was ensuring data security, which I addressed by implementing OAuth for authentication and authorization."

Data Modeling and Architecture

1. How do you approach data modeling for a new project?

Data modeling is a critical skill for a Data Engineer, and interviewers will want to understand your methodology.

How to Answer

Describe your process for gathering requirements, designing the model, and validating it with stakeholders.

Example

"I start by collaborating with stakeholders to gather requirements and understand the business context. Then, I create an initial conceptual model, followed by a logical model that includes entity relationships. Finally, I validate the model with the team to ensure it meets all use cases before implementation."

2. What are the key considerations when designing a data lake?

This question assesses your understanding of data storage solutions and their architecture.

How to Answer

Discuss the factors that influence the design of a data lake, such as data types, access patterns, and governance.

Example

"When designing a data lake, I consider the types of data we will store, including structured and unstructured data. I also focus on access patterns to ensure efficient querying and retrieval, and I implement governance policies to manage data quality and compliance."

3. Can you explain the concept of event-driven architecture?

Understanding event-driven architecture is essential for modern data solutions, especially in real-time processing.

How to Answer

Define event-driven architecture and discuss its benefits and use cases.

Example

"Event-driven architecture is a design pattern where system components communicate through events, allowing for asynchronous processing. This approach is beneficial for real-time applications, as it enables systems to react to events as they occur, improving responsiveness and scalability."

4. Describe a challenging data integration project you worked on.

This question allows you to showcase your problem-solving skills and technical expertise.

How to Answer

Share a specific project, the challenges you faced, and how you overcame them.

Example

"I worked on integrating data from multiple sources into a centralized data warehouse. The challenge was dealing with inconsistent data formats. I implemented a data transformation layer that standardized the data before ingestion, which streamlined the integration process and improved data quality."

5. How do you optimize data storage and retrieval performance?

Performance optimization is crucial for data systems, and interviewers will want to know your strategies.

How to Answer

Discuss the techniques you use to enhance performance, such as indexing, partitioning, or caching.

Example

"I optimize data storage by implementing partitioning strategies based on query patterns, which significantly reduces retrieval times. Additionally, I use indexing on frequently accessed columns to speed up query performance, and I regularly analyze query execution plans to identify further optimization opportunities."