Acrisure Technology Group Data Engineer Interview Questions + Guide in 2025

Acrisure Technology Group (ATG) is a dynamic, AI-driven organization aiming to revolutionize the insurance industry through innovative software solutions.

The Data Engineer plays a crucial role within the Business Intelligence team, which focuses on unifying data across the organization to enhance strategic, tactical, and operational decision-making. This position involves designing and developing complex ETL (Extract, Transform, Load) processes that populate a data lake and structured data warehouse, ultimately providing data for machine learning, artificial intelligence, and business intelligence teams. A successful candidate will possess strong expertise in SQL, Python, and ETL processes, as well as experience with data modeling and analytics. Additionally, the role requires mentoring junior developers and ensuring adherence to quality standards throughout the development cycle.

In this position, collaboration with analysts and other data engineers is vital for identifying improvement opportunities and optimizing the company's data products and services. Familiarity with cloud technologies, particularly Google Cloud, and experience with frameworks such as Kubernetes, Dataflow, and various database technologies are essential.

This guide will equip you with the knowledge and insights necessary to prepare for your interview, giving you a competitive edge in demonstrating your fit for the Data Engineer role at Acrisure Technology Group.

The interview process for a Data Engineer at Acrisure Technology Group is structured to assess both technical skills and cultural fit within the organization. It typically consists of several stages, each designed to evaluate different aspects of a candidate's qualifications and experience.

1. Initial HR Screening

The process begins with a 30-minute phone interview with an HR representative. This initial screening focuses on understanding your background, qualifications, and motivations for applying to Acrisure. The HR representative will ask about your experience with data engineering, your familiarity with relevant technologies, and your career aspirations. This conversation is also an opportunity for you to ask questions about the company culture and the role.

2. Technical Interview

Following the HR screening, candidates typically participate in a technical interview, which may be conducted via video conference. This interview is often led by a senior data engineer or a technical manager. During this session, you can expect to discuss your experience with ETL processes, data modeling, and the specific technologies mentioned in the job description, such as SQL, Python, and cloud platforms like Azure. You may also be asked to solve technical problems or case studies that demonstrate your analytical and problem-solving skills.

3. Team Interview

The next step usually involves a panel interview with members of the data engineering team. This session is designed to assess how well you would fit within the team and your ability to collaborate with others. Expect to answer situational questions that explore your past experiences, such as how you have handled challenges in previous projects or how you approach mentoring junior developers. This round may also include discussions about your understanding of data quality, usability, and business rule standards.

4. Final Interview with Leadership

In some cases, candidates may have a final interview with higher-level management or executives. This interview focuses on your long-term vision, alignment with the company's goals, and your potential contributions to the team. You may be asked to present a strategy or a project you have worked on, showcasing your ability to communicate complex ideas effectively.

5. Offer and Negotiation

If you successfully navigate the interview stages, you may receive a verbal offer shortly after the final interview. The written offer will follow, detailing the terms of employment. Be prepared to discuss your salary expectations and any other benefits you may be interested in.

As you prepare for your interview, consider the specific skills and experiences that will be relevant to the questions you may encounter. Next, let's delve into the types of questions that candidates have faced during the interview process.

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

Understand the Interview Structure

The interview process at Acrisure Technology Group typically consists of multiple stages, starting with an initial HR screening followed by interviews with the hiring manager and team members. Familiarize yourself with this structure and prepare accordingly. Be ready to discuss your qualifications and experiences in detail, as well as how they align with the company's mission and values.

Showcase Your Technical Expertise

As a Data Engineer, you will be expected to demonstrate a strong command of SQL, Python, and ETL processes. Brush up on your technical skills, particularly in SQL and data modeling, as these are crucial for the role. Be prepared to discuss your experience with data lakes, data warehouses, and any relevant frameworks or tools you have used, such as Google Cloud, Kubernetes, and BigQuery. Consider preparing a few examples of complex ETL processes you have designed or implemented in the past.

Prepare for Behavioral Questions

Expect behavioral questions that assess your problem-solving abilities and teamwork skills. Use the STAR (Situation, Task, Action, Result) method to structure your responses. For instance, you might be asked to describe a time when you went above and beyond for a project or how you handled a challenging situation with a team member. Reflect on your past experiences and be ready to share specific examples that highlight your skills and contributions.

Emphasize Your Collaborative Spirit

Acrisure values collaboration and teamwork, so be prepared to discuss how you have worked effectively with others in previous roles. Highlight your experience mentoring junior developers or collaborating with cross-functional teams. This will demonstrate your ability to contribute positively to the team dynamic and support the growth of others.

Align with Company Culture

Acrisure is a fast-paced, AI-driven company focused on innovation in the insurance industry. Research the company's mission and values, and think about how your personal values align with theirs. Be ready to articulate why you want to work at Acrisure and how you can contribute to their goals. This alignment will help you stand out as a candidate who is not only technically proficient but also culturally fit.

Ask Insightful Questions

Prepare thoughtful questions to ask your interviewers. This shows your genuine interest in the role and the company. Inquire about the team dynamics, the challenges they face, or how they measure success in the Data Engineering team. Asking about opportunities for professional development or the company's future direction can also provide valuable insights and demonstrate your long-term interest in the position.

Follow Up Professionally

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 resonated with you. This not only shows your professionalism but also keeps you top of mind as they make their decision.

By following these tips, you can present yourself as a well-prepared and enthusiastic candidate who is ready to contribute to Acrisure Technology Group's mission and success. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Acrisure Technology Group. The interview process will likely focus on your technical skills, experience with data engineering concepts, and your ability to work collaboratively within a team. Be prepared to discuss your past projects, your approach to problem-solving, and your understanding of the technologies and methodologies relevant to the role.

Technical Skills

1. Can you explain the ETL process and its importance in data engineering?

Understanding the ETL (Extract, Transform, Load) process is crucial for a Data Engineer, as it is the backbone of data integration and management.

How to Answer

Discuss the steps involved in ETL, emphasizing how each step contributes to data quality and accessibility for analysis.

Example

“The ETL process involves extracting data from various sources, transforming it into a suitable format, and loading it into a data warehouse. This process is vital as it ensures that data is clean, consistent, and readily available for analysis, which ultimately drives informed business decisions.”

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

SQL is a fundamental skill for data engineers, and demonstrating your proficiency can set you apart.

How to Answer

Share a specific example of a complex SQL query you wrote, explaining the context and the outcome.

Example

“I have extensive experience with SQL, including writing complex queries involving multiple joins and subqueries. For instance, I once created a query that aggregated sales data across multiple regions and time periods, which helped the marketing team identify trends and optimize their strategies.”

3. How do you ensure data quality and integrity in your ETL processes?

Data quality is critical in data engineering, and interviewers will want to know your strategies for maintaining it.

How to Answer

Discuss the methods you use to validate and clean data during the ETL process.

Example

“I implement data validation checks at each stage of the ETL process, such as verifying data types and ranges during extraction and using automated tests to catch anomalies before loading. Additionally, I regularly audit the data to ensure ongoing integrity.”

4. Describe your experience with cloud platforms, particularly Google Cloud.

Given Acrisure's use of Google Cloud, familiarity with this platform is essential.

How to Answer

Highlight your experience with Google Cloud services, particularly those relevant to data engineering.

Example

“I have worked extensively with Google Cloud, particularly BigQuery for data warehousing and Dataflow for stream processing. I utilized these tools to build scalable data pipelines that efficiently handled large datasets, significantly improving our data processing times.”

Data Modeling and Architecture

5. Can you explain the difference between a data lake and a data warehouse?

Understanding the distinctions between these two concepts is vital for a Data Engineer.

How to Answer

Clarify the purposes and structures of data lakes and data warehouses.

Example

“A data lake is designed to store vast amounts of raw data in its native format, allowing for flexible data exploration. In contrast, a data warehouse is structured for efficient querying and analysis, storing processed data in a format optimized for reporting and business intelligence.”

6. What strategies do you use for data modeling?

Data modeling is a key aspect of data engineering, and interviewers will want to know your approach.

How to Answer

Discuss your methodology for creating data models, including any tools or frameworks you use.

Example

“I typically start with a thorough analysis of business requirements to create conceptual models. I then use tools like ER/Studio to develop logical and physical data models, ensuring they align with the overall architecture and support efficient data retrieval.”

Problem-Solving and Collaboration

7. Describe a challenging data engineering problem you faced and how you resolved it.

This question assesses your problem-solving skills and resilience.

How to Answer

Share a specific challenge, your thought process, and the solution you implemented.

Example

“I once faced a challenge with data latency in our ETL process, which was affecting reporting accuracy. I analyzed the pipeline and identified bottlenecks in data transformation. By optimizing the transformation logic and implementing parallel processing, I reduced the latency by 50%, significantly improving our reporting timelines.”

8. How do you prioritize tasks when managing multiple projects?

Time management is crucial in a fast-paced environment.

How to Answer

Explain your approach to prioritization and any tools you use to manage your workload.

Example

“I prioritize tasks based on project deadlines and business impact. I use project management tools like Jira to track progress and ensure that I allocate time effectively across projects. Regular check-ins with stakeholders also help me adjust priorities as needed.”

Team Dynamics

9. How do you mentor junior developers in your team?

Mentoring is an important aspect of the role, especially in a collaborative environment.

How to Answer

Discuss your mentoring style and any specific strategies you employ.

Example

“I believe in hands-on mentoring, where I pair with junior developers on projects to provide guidance and support. I also encourage them to take ownership of smaller tasks, allowing them to learn through experience while providing constructive feedback along the way.”

10. How do you handle conflicts within a team?

Team dynamics can be challenging, and your approach to conflict resolution is important.

How to Answer

Share your conflict resolution strategy, emphasizing communication and collaboration.

Example

“When conflicts arise, I prioritize open communication. I encourage team members to express their concerns and facilitate a discussion to find common ground. By focusing on the project goals and fostering a collaborative environment, we can often resolve conflicts constructively.”