Delivery Hero Data Engineer Interview Questions + Guide in 2025

Delivery Hero is the world's largest food-ordering network, innovating and expanding into new verticals such as groceries and pharmacies while operating across 40+ countries.

As a Data Engineer at Delivery Hero, you will play a pivotal role in building and maintaining scalable data systems and infrastructure to process and analyze vast amounts of customer data in real-time. Your primary responsibilities will include designing and developing distributed systems, ensuring low-latency APIs, and creating batch data pipelines to support data scientists and analysts. A strong emphasis on engineering best practices, system architecture, and mentoring team members will be essential to your success. Ideal candidates will possess a solid understanding of cloud infrastructure, experience with resilient API design, and a passion for clean, efficient code. Embracing a culture of experimentation and collaboration aligned with Delivery Hero’s values will set you on the path to delivering an amazing customer experience.

This guide will help you prepare for the interview by providing insights into the skills and traits that will be most valuable to demonstrate during the process.

The interview process for a Data Engineer at Delivery Hero is designed to assess both technical skills and cultural fit within the team. It typically consists of several structured rounds that evaluate your expertise in data engineering, problem-solving abilities, and collaborative mindset.

1. Initial Screening

The process begins with an initial screening, usually a 30-minute conversation with a recruiter. This discussion focuses on your background, skills, and motivations for applying to Delivery Hero. The recruiter will also provide insights into the company culture and the specifics of the Data Engineer role, ensuring that you have a clear understanding of what to expect.

2. Technical Assessment

Following the initial screening, candidates typically undergo a technical assessment. This may involve a take-home assignment where you will be tasked with SQL questions and possibly creating Tableau dashboards. The goal is to evaluate your practical skills in data manipulation and visualization, which are crucial for the role.

3. Technical Interviews

After the technical assessment, candidates will participate in one or more technical interviews. These interviews are often conducted by senior team members or hiring managers and focus on your knowledge of distributed systems, API development, and cloud infrastructure. Expect to discuss your previous projects, the technologies you used, and how you approached problem-solving in those scenarios.

4. Case Study Presentation

In some instances, candidates may be required to complete a case study that they will present to the team. This step allows you to demonstrate your analytical skills and your ability to communicate complex ideas effectively. The presentation will typically involve discussing your findings and the methodologies you employed during the analysis.

5. Cultural Fit Interview

The final round often includes a cultural fit interview, where you will meet with team members to discuss your values, work style, and how you align with Delivery Hero's mission. This is an opportunity for both you and the team to assess whether you would thrive in the company’s collaborative and fast-paced environment.

Throughout the process, candidates are encouraged to ask questions and engage with their interviewers, as this reflects your interest in the role and the company.

Now that you have an understanding of the interview process, let’s delve into the specific questions that may arise during your interviews.

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

Understand the Interview Structure

Delivery Hero's interview process typically involves multiple stages, including an initial HR discussion, technical interviews, and a case study presentation. Familiarize yourself with this structure so you can prepare accordingly. Expect to discuss your previous projects in detail, as well as your technical skills, particularly in SQL and Python. Being well-prepared for each stage will help you navigate the process smoothly.

Showcase Your Technical Skills

Given the emphasis on SQL and Python in the role, ensure you are comfortable with both. Prepare for technical questions that may involve writing SQL queries or discussing your experience with data pipelines. Additionally, be ready to tackle questions related to algorithms and data structures, as these are crucial for building scalable systems. Practicing coding challenges and reviewing your past projects will give you the confidence to demonstrate your expertise.

Prepare for the Case Study

The case study is a significant part of the interview process. You may be asked to analyze data and present your findings. Make sure to practice presenting your analysis clearly and concisely, as communication is key. Focus on how your insights can drive business decisions and improve customer experiences. Use visual aids like Tableau dashboards to enhance your presentation and make your findings more accessible.

Emphasize Collaboration and Team Fit

Delivery Hero values teamwork and collaboration. Be prepared to discuss how you have worked effectively in teams in the past, particularly in agile environments. Highlight your ability to communicate with stakeholders and your willingness to mentor others. This will demonstrate that you not only possess the technical skills but also the interpersonal skills necessary to thrive in their culture.

Be Ready for Behavioral Questions

Expect questions that assess your fit within the company culture. Delivery Hero looks for candidates who are proactive, willing to learn, and can adapt to a fast-paced environment. Prepare examples from your past experiences that showcase your problem-solving abilities, adaptability, and how you handle challenges. This will help you convey that you align with their values and can contribute positively to the team.

Follow Up Professionally

After your interviews, it’s important to follow up with a thank-you email to express your appreciation for the opportunity. This not only shows your professionalism but also reinforces your interest in the role. If you experience delays in communication, remain patient but proactive in seeking updates. This reflects your commitment and enthusiasm for the position.

By following these tips, you will be well-prepared to make a strong impression during your interview at Delivery Hero. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Delivery Hero. The interview process will likely focus on your technical skills, particularly in SQL, algorithms, and Python, as well as your experience with data systems and cloud infrastructure. Be prepared to discuss your past projects and how they relate to the role.

Technical Skills

1. Can you explain the difference between batch processing and stream processing?

Understanding the distinction between these two processing methods is crucial for a Data Engineer, especially in a real-time data environment.

How to Answer

Discuss the characteristics of both processing types, including their use cases and advantages. Highlight scenarios where one might be preferred over the other.

Example

"Batch processing involves processing large volumes of data at once, which is ideal for tasks like monthly reporting. In contrast, stream processing handles data in real-time, allowing for immediate insights, which is essential for applications like fraud detection or real-time analytics."

2. Describe a project where you built a data pipeline. What challenges did you face?

This question assesses your practical experience and problem-solving skills in building data systems.

How to Answer

Outline the project scope, the technologies used, and the specific challenges encountered. Emphasize how you overcame these challenges.

Example

"I built a data pipeline to aggregate user activity data from multiple sources. One challenge was ensuring data consistency across different formats. I implemented a schema validation step to standardize incoming data, which significantly improved the reliability of our analytics."

3. How do you ensure the reliability and fault tolerance of your data systems?

Reliability is key in data engineering, and interviewers want to know your strategies for maintaining system integrity.

How to Answer

Discuss techniques such as data replication, error handling, and monitoring. Provide examples of how you've implemented these strategies in past projects.

Example

"I use data replication across multiple nodes to ensure availability. Additionally, I implement comprehensive logging and alerting systems to monitor for failures, allowing for quick recovery and minimal downtime."

4. What is your experience with cloud platforms, and how have you utilized them in your projects?

Cloud infrastructure is a significant aspect of modern data engineering, and your familiarity with it is essential.

How to Answer

Mention specific cloud services you've used, such as AWS or Google Cloud, and describe how they were integrated into your projects.

Example

"I have extensive experience with AWS, particularly with services like S3 for storage and Lambda for serverless computing. In a recent project, I used AWS Glue to automate ETL processes, which streamlined our data ingestion and processing workflows."

5. Can you explain how you would optimize a slow-running SQL query?

SQL proficiency is critical for a Data Engineer, and optimization skills are highly valued.

How to Answer

Discuss common optimization techniques such as indexing, query restructuring, and analyzing execution plans.

Example

"I would start by analyzing the execution plan to identify bottlenecks. If a query is slow due to table scans, I would consider adding indexes on frequently queried columns. Additionally, I would look for opportunities to simplify joins or reduce the dataset size with WHERE clauses."

Algorithms and Data Structures

1. What data structures would you use to implement a real-time analytics system?

This question tests your understanding of data structures in the context of performance and efficiency.

How to Answer

Discuss the data structures that are best suited for real-time analytics, such as queues or hash maps, and explain why.

Example

"I would use a combination of queues for incoming data streams and hash maps for quick lookups. Queues allow for efficient processing of data as it arrives, while hash maps enable fast access to aggregated results."

2. How would you handle data deduplication in a streaming data pipeline?

Deduplication is a common challenge in data engineering, especially with real-time data.

How to Answer

Explain your approach to identifying and removing duplicates, including any algorithms or techniques you would use.

Example

"I would implement a deduplication strategy using a combination of timestamps and unique identifiers. By maintaining a cache of recently processed records, I can quickly check for duplicates before inserting new data into the database."

3. Can you describe a time when you had to optimize an algorithm for performance?

This question assesses your practical experience with algorithms and your ability to improve them.

How to Answer

Provide a specific example of an algorithm you optimized, detailing the initial performance issues and the steps you took to enhance it.

Example

"I was tasked with optimizing a sorting algorithm that was taking too long on large datasets. I switched from a basic bubble sort to a quicksort implementation, which reduced the time complexity from O(n^2) to O(n log n), significantly improving performance."

4. What is your approach to testing and validating data pipelines?

Testing is crucial in data engineering to ensure data quality and system reliability.

How to Answer

Discuss your methods for testing data pipelines, including unit tests, integration tests, and data validation techniques.

Example

"I implement unit tests for individual components of the pipeline and use integration tests to ensure that data flows correctly through the entire system. Additionally, I perform data validation checks to compare incoming data against expected formats and values."

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

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

How to Answer

Mention specific resources, communities, or events you engage with to stay informed about industry trends.

Example

"I regularly follow industry blogs, participate in online forums, and attend conferences related to data engineering. I also take advantage of online courses to learn about new tools and technologies, ensuring that I stay current in this rapidly evolving field."