Avant Data Engineer Interview Questions + Guide in 2025

Avant is a dynamic financial technology company focused on reshaping the digital banking experience through innovative solutions and customer-centric services.

As a Data Engineer at Avant, you will play a pivotal role in building and enhancing data models that support various business initiatives. Your primary responsibilities will include modeling new data sets, working with internal stakeholders to define business requirements, and ensuring high-quality data governance across the organization's data platform. You will leverage frameworks for data curation and pipeline automation to support operational processes and decision-making. A successful Data Engineer at Avant exhibits proficiency in SQL, data modeling, pipeline automation, and is well-versed in technologies like Databricks and DBT. Equally important is your ability to communicate effectively, work collaboratively with teams, and maintain a detail-oriented approach to data management.

This guide will equip you with essential insights about the role and expectations at Avant, helping you to prepare effectively for your interview and stand out as a candidate aligned with the company's values and mission.

The interview process for a Data Engineer position at Avant is structured to assess both technical skills and cultural fit within the company. It typically consists of several key stages:

1. Application and Initial Screening

The process begins with an online application, where candidates submit their resumes and cover letters. Following this, a recruiter will reach out for an initial screening call. This conversation usually lasts about 30 minutes and focuses on understanding the candidate's background, skills, and motivations for applying to Avant. The recruiter will also provide insights into the company culture and the specifics of the role.

2. Technical Assessment

After the initial screening, candidates are often required to complete a technical assessment. This may take the form of a coding challenge or a take-home project that evaluates proficiency in relevant technologies, particularly Python and SQL. Candidates should be prepared to demonstrate their problem-solving abilities and technical knowledge through practical exercises.

3. Behavioral Interview

Following the technical assessment, candidates typically participate in a behavioral interview. This round is designed to gauge how well candidates align with Avant's core values, such as collaboration, problem-solving, and initiative. Interviewers will ask about past experiences, challenges faced, and how candidates have worked in team settings.

4. Onsite or Virtual Interview

The final stage usually involves a more in-depth onsite or virtual interview, which can last up to two hours. This interview is often divided into multiple segments, each led by different team members. Candidates can expect to engage in discussions that cover case studies, technical questions, and assessments of their take-home project. Interviewers will evaluate both technical skills and the ability to communicate complex ideas effectively.

Throughout the interview process, candidates should be prepared for a mix of technical and behavioral questions, as well as discussions about their previous work experiences and how they can contribute to Avant's mission.

Next, let's explore the specific interview questions that candidates have encountered during this process.

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

Understand the Company Culture

Avant values authenticity, collaboration, and problem-solving. Familiarize yourself with these core values and think about how your personal experiences align with them. During the interview, demonstrate your ability to work as part of a team and your commitment to delivering high-quality solutions. Be prepared to share examples of how you've collaborated with others to solve complex problems in your previous roles.

Prepare for Technical Challenges

Given the emphasis on Python and data modeling, ensure you are well-versed in these areas. Review common data engineering concepts and be ready to discuss your experience with tools like Databricks and DBT. Practice coding challenges, particularly those that involve data manipulation and transformation. The interview may include practical assessments, so be prepared to showcase your problem-solving skills in real-time.

Be Ready for Behavioral Questions

Expect behavioral questions that assess your ability to work independently and as part of a team. Use the STAR (Situation, Task, Action, Result) method to structure your responses. Reflect on past experiences where you demonstrated initiative, overcame challenges, or mentored others. This will help you convey your fit for Avant's collaborative and learning-oriented culture.

Engage with Your Interviewers

Interviews at Avant may involve multiple team members, so take the opportunity to engage with each interviewer. Ask insightful questions about their experiences and the projects they are working on. This not only shows your interest in the role but also helps you gauge the team dynamics and culture. Remember, interviews are a two-way street, and your questions can help you determine if Avant is the right fit for you.

Stay Calm and Adaptable

Interviews can sometimes be unpredictable, as noted in candidate experiences. If you encounter an interviewer with a low energy level or an unconventional style, remain calm and adaptable. Focus on clearly articulating your thought process and solutions. If you feel uncertain about an interviewer’s feedback, don’t hesitate to ask clarifying questions to ensure you understand their expectations.

Follow Up Thoughtfully

After the interview, send a personalized thank-you note to express your appreciation for the opportunity to interview. Mention specific topics discussed during the interview to reinforce your interest in the role and the company. This not only demonstrates professionalism but also keeps you top of mind as they make their hiring decisions.

By preparing thoroughly and aligning your approach with Avant's values and expectations, you can position yourself as a strong candidate for the Data Engineer role. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Avant. The interview process will likely assess your technical skills in data engineering, your problem-solving abilities, and your capacity to collaborate with various stakeholders. Be prepared to demonstrate your proficiency in Python, SQL, data modeling, and cloud technologies, as well as your understanding of data governance and quality assurance.

Technical Skills

1. Can you explain how you would move data from an on-premises PostgreSQL database to a cloud environment?

This question assesses your understanding of data migration processes and cloud technologies.

How to Answer

Discuss the steps involved in the migration process, including data extraction, transformation, and loading (ETL) into the cloud. Mention any tools or services you would use, such as AWS Data Migration Service or Google Cloud Dataflow.

Example

"I would start by assessing the data structure and volume in the PostgreSQL database. Then, I would use an ETL tool like Google Cloud Dataflow to extract the data, transform it as needed, and load it into a cloud storage solution like Google Cloud Storage or BigQuery. Ensuring data integrity and security during the transfer would be a priority."

2. Describe a challenging data modeling project you worked on. What were the key considerations?

This question evaluates your experience with data modeling and your ability to handle complex projects.

How to Answer

Highlight the project’s objectives, the challenges faced, and how you addressed them. Discuss the importance of stakeholder engagement and understanding business requirements.

Example

"I worked on a project to model customer data for a new analytics platform. The challenge was integrating data from multiple sources while ensuring data quality. I engaged with stakeholders to define clear requirements and used a dimensional modeling approach to create a star schema that met both analytical and operational needs."

3. How do you ensure data quality and governance in your projects?

This question focuses on your understanding of data governance practices.

How to Answer

Discuss the frameworks and processes you implement to maintain data quality, such as validation checks, data profiling, and adherence to governance policies.

Example

"I implement data quality checks at various stages of the ETL process, including validation rules and automated testing. Additionally, I ensure compliance with governance policies by documenting data lineage and maintaining a data catalog that provides visibility into data sources and transformations."

4. What is your experience with dbt (data build tool) and how have you used it in your projects?

This question assesses your familiarity with dbt and its application in data engineering.

How to Answer

Explain how you have utilized dbt for data transformation and modeling, emphasizing its role in maintaining version control and documentation.

Example

"I have used dbt extensively to manage data transformations in my projects. It allows me to write modular SQL code, which I can version control and document effectively. This has streamlined our data pipeline and improved collaboration among team members."

5. Can you discuss a time when you had to troubleshoot a data pipeline issue? What steps did you take?

This question evaluates your problem-solving skills and technical troubleshooting abilities.

How to Answer

Describe the issue, the steps you took to identify the root cause, and how you resolved it. Highlight your analytical skills and attention to detail.

Example

"Once, I encountered a data pipeline failure due to a schema change in the source database. I quickly reviewed the logs to identify the error and traced it back to the transformation step. I updated the transformation logic to accommodate the new schema and implemented alerts to catch similar issues in the future."

Collaboration and Communication

1. How do you approach gathering requirements from stakeholders for a data project?

This question assesses your communication and collaboration skills.

How to Answer

Discuss your methods for engaging with stakeholders, such as conducting interviews, workshops, or surveys to gather their needs and expectations.

Example

"I typically start by scheduling meetings with key stakeholders to understand their data needs. I use a combination of interviews and workshops to facilitate discussions and gather requirements. This collaborative approach ensures that the final data model aligns with their expectations."

2. Describe a situation where you had to explain a complex technical concept to a non-technical audience.

This question evaluates your ability to communicate effectively with diverse audiences.

How to Answer

Provide an example of a time you simplified a technical concept and the methods you used to ensure understanding.

Example

"I once had to explain our data pipeline architecture to a group of marketing professionals. I used visual aids and analogies to break down the components and their functions, ensuring they understood how data flows from source to reporting. Their positive feedback indicated that they grasped the concept well."

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

This question assesses your organizational and time management skills.

How to Answer

Discuss your approach to prioritization, including how you assess project urgency and importance, and any tools you use to manage your workload.

Example

"I prioritize tasks based on project deadlines and stakeholder impact. I use project management tools like Trello to track progress and ensure that I allocate time effectively. Regular check-ins with my team also help me adjust priorities as needed."

4. Can you give an example of how you mentored a colleague or team member?

This question evaluates your leadership and mentoring abilities.

How to Answer

Share a specific instance where you provided guidance or support to a colleague, focusing on the outcome of your mentorship.

Example

"I mentored a junior data engineer who was struggling with SQL queries. I organized weekly sessions to review concepts and worked on real-world examples together. Over time, I saw significant improvement in their skills, and they became more confident in their work."

5. How do you stay updated with the latest trends and technologies in data engineering?

This question assesses your commitment to continuous learning and professional development.

How to Answer

Discuss the resources you use to stay informed, such as online courses, webinars, industry blogs, or professional networks.

Example

"I regularly follow industry blogs and participate in webinars to stay updated on the latest trends in data engineering. I also engage with online communities like LinkedIn and attend local meetups to network with other professionals and share knowledge."