84.51 Degrees Data Engineer Interview Questions + Guide in 2025

84.51° is a retail data science and insights company focused on enhancing customer experiences through data-driven solutions.

As a Data Engineer at 84.51°, you will play a crucial role in transforming vast amounts of retail data into actionable insights that drive personalized customer experiences. Key responsibilities include developing and maintaining complex data solutions that support commercial data pipelines, ensuring data security and integrity, and collaborating with cross-functional teams to translate business requirements into technical specifications. A strong background in data warehousing, ETL processes, and business intelligence tools is essential. You will also utilize your proficiency in SQL and familiarity with Agile methodologies to implement and optimize data solutions, all while mentoring junior engineers and driving improvements in development practices.

This guide will help you prepare for your interview by providing insights into the skills and experiences that align with 84.51°'s values and operational processes, giving you a competitive edge in the hiring process.

The interview process for a Data Engineer position at 84.51 Degrees is designed to assess both technical skills and cultural fit within the company. The process typically unfolds in several structured stages:

1. Initial Screening

The first step is an initial screening interview, which is usually conducted over the phone or via video call. During this conversation, a recruiter will discuss your background, interest in the role, and alignment with the company’s values. This is also an opportunity for you to ask questions about the company and the position.

2. Technical Assessment

Following the initial screening, candidates often participate in a technical assessment. This may involve a coding challenge or a problem-solving exercise that tests your proficiency in SQL and other relevant programming languages. You might be asked to solve specific data-related problems or to explain your thought process while tackling a technical question. The focus here is on your analytical skills and ability to work through complex scenarios.

3. Behavioral Interview

The next stage typically involves a behavioral interview, where you will engage in a more conversational format with one or more interviewers. Expect questions that explore your past experiences, teamwork, and how you handle challenges. This part of the interview is crucial for assessing your fit within the company culture and your ability to collaborate with others.

4. Onsite or Final Interview

The final interview stage may take place onsite or virtually, depending on the circumstances. This round often includes multiple interviews with different team members, including technical and managerial staff. You may be asked to discuss your previous projects in detail, demonstrate your understanding of data engineering concepts, and tackle case studies relevant to the role. This is also a chance for you to showcase your problem-solving skills and how you approach data-related challenges.

5. Offer and Feedback

After the final interviews, candidates can expect prompt feedback regarding their application status. If selected, you will receive an offer, often accompanied by a discussion about the role's responsibilities and expectations.

As you prepare for your interview, consider the types of questions that may arise during each stage of the process.

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

Understand the Company’s Mission and Values

Before your interview, take the time to familiarize yourself with 84.51°'s mission and the specific role of data engineering within the company. Understand how the company leverages data to enhance customer experiences and support its partners. This knowledge will not only help you answer questions more effectively but also demonstrate your genuine interest in the company and its objectives.

Prepare for Behavioral Questions

Expect a mix of behavioral and technical questions during your interview. Use the STAR (Situation, Task, Action, Result) method to structure your responses to behavioral questions. Be ready to discuss your past experiences, particularly those that highlight your problem-solving skills and ability to work collaboratively in a team. Given the emphasis on teamwork at 84.51°, showcasing your interpersonal skills will be crucial.

Brush Up on Technical Skills

Given the technical nature of the Data Engineer role, ensure you are well-versed in SQL and algorithms, as these are critical components of the interview process. Practice solving SQL problems, focusing on complex queries, joins, and data manipulation. Additionally, be prepared to discuss your experience with data warehousing concepts and ETL processes, as these are essential for the role.

Showcase Your Problem-Solving Abilities

During technical interviews, you may be presented with case studies or problem-solving scenarios. Approach these questions methodically, explaining your thought process as you work through the problem. Interviewers at 84.51° are interested in how you arrive at a solution, not just the final answer. Be prepared to discuss your reasoning and any assumptions you make along the way.

Engage with Your Interviewers

The interview process at 84.51° is described as conversational and friendly. Take advantage of this by engaging with your interviewers. 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 if the company culture aligns with your values.

Be Ready for a Fast-Paced Process

Candidates have noted that the interview process at 84.51° can be quick and straightforward. Be prepared for a fast-paced interview environment, and ensure you have your availability clear for follow-up interviews. This readiness will demonstrate your enthusiasm and adaptability, qualities that are valued in a dynamic work environment.

Highlight Your Passion for Data

Express your passion for data and how it drives your work. Discuss any personal projects or experiences that showcase your enthusiasm for data engineering. This can help you stand out as a candidate who is not only technically proficient but also genuinely invested in the field.

Follow Up Thoughtfully

After your interview, consider sending a thank-you email to your interviewers. In your message, reiterate your interest in the position and mention specific topics discussed during the interview that resonated with you. This thoughtful follow-up can leave a positive impression and reinforce your enthusiasm for the role.

By following these tips, you can approach your interview with confidence and a clear strategy, increasing your chances of success at 84.51°. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at 84.51°. The interview process will likely assess your technical skills, problem-solving abilities, and cultural fit within the company. Be prepared to discuss your past experiences, technical knowledge, and how you approach data-related challenges.

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 fundamental to data integration and management.

How to Answer

Discuss the stages of ETL, emphasizing how each step contributes to preparing data for analysis and reporting. Highlight its significance in ensuring data quality and accessibility.

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 supports informed decision-making.”

2. Describe a complex SQL query you have written and its purpose.

SQL proficiency is essential for data manipulation and retrieval in this role.

How to Answer

Provide a specific example of a SQL query you wrote, explaining the context, the data involved, and the outcome of your query.

Example

“I once wrote a complex SQL query to analyze customer purchase patterns. The query involved multiple joins across several tables to aggregate data on customer transactions, which helped identify trends and inform marketing strategies.”

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

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

How to Answer

Discuss the methods you use to validate and clean data, as well as any tools or frameworks you employ to monitor data quality.

Example

“I implement data validation checks at various stages of the ETL process, using automated scripts to identify anomalies. Additionally, I regularly conduct data audits to ensure accuracy and consistency, which helps maintain high data quality standards.”

4. What is your experience with cloud-based data solutions?

Given the increasing reliance on cloud technologies, familiarity with cloud platforms is important.

How to Answer

Share your experience with specific cloud services, detailing how you have utilized them in your projects.

Example

“I have worked extensively with AWS and Azure for deploying data pipelines. For instance, I used AWS Glue for ETL processes and Azure Data Lake for storing large datasets, which allowed for scalable and efficient data management.”

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

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

How to Answer

Define data warehousing and discuss its advantages, particularly in relation to business intelligence and analytics.

Example

“Data warehousing is the process of collecting and managing data from various sources to provide meaningful business insights. Its benefits include improved data analysis capabilities, historical data storage for trend analysis, and enhanced reporting efficiency.”

Problem-Solving and Analytical Skills

1. Describe a time when you faced a significant data challenge and how you resolved it.

This question assesses your problem-solving skills and resilience in the face of obstacles.

How to Answer

Use the STAR method (Situation, Task, Action, Result) to structure your response, focusing on the challenge and your approach to overcoming it.

Example

“In a previous project, I encountered inconsistent data formats across multiple sources. I led a team to standardize the data formats using a combination of Python scripts and SQL transformations, which ultimately improved our data integration process and reduced errors.”

2. How would you approach designing a data pipeline for a new project?

This question evaluates your design thinking and technical planning skills.

How to Answer

Outline the steps you would take, from understanding requirements to selecting technologies and ensuring scalability.

Example

“I would start by gathering requirements from stakeholders to understand the data sources and desired outcomes. Then, I would design the pipeline architecture, selecting appropriate tools for ETL processes, and ensure it is scalable by using cloud services. Finally, I would implement monitoring to track performance and data quality.”

3. What strategies do you use to optimize database performance?

Performance optimization is key in data engineering, and interviewers will want to know your techniques.

How to Answer

Discuss specific strategies you have employed, such as indexing, query optimization, or partitioning.

Example

“I focus on indexing frequently queried columns and optimizing SQL queries to reduce execution time. Additionally, I implement database partitioning to improve performance for large datasets, which has significantly enhanced query response times in my previous projects.”

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

Continuous learning is vital in the tech field, and interviewers will appreciate your commitment to professional development.

How to Answer

Mention specific resources, communities, or courses you engage with to keep your skills current.

Example

“I regularly follow industry blogs, participate in online forums, and attend webinars to stay informed about the latest trends in data engineering. I also take online courses to deepen my knowledge of emerging technologies, such as cloud computing and machine learning.”

5. Can you give an example of how you have used data visualization to communicate insights?

Data visualization is an important aspect of data engineering, and interviewers will want to see your ability to convey complex information clearly.

How to Answer

Provide a specific instance where you used data visualization tools to present findings to stakeholders.

Example

“I created a series of interactive dashboards using Power BI to visualize customer behavior data. This allowed stakeholders to easily identify trends and make data-driven decisions, ultimately leading to a successful marketing campaign.”