North Highland Data Engineer Interview Questions + Guide in 2025

North Highland is a leading change and transformation consultancy committed to making meaningful change happen for its clients.

As a Data Engineer at North Highland, you will play a pivotal role in designing and implementing data-driven solutions that fulfill business objectives while ensuring data integrity and accessibility. The key responsibilities of this role encompass developing scalable data pipelines, managing data architecture, and ensuring the quality of data across various systems. You will collaborate closely with cross-functional teams, including data scientists and analysts, to support advanced analytics initiatives and drive insights that transform client operations. A strong technical foundation in cloud platforms (particularly Google Cloud Platform), big data technologies, and programming languages such as Python or Java will be essential for success in this role. Additionally, having an understanding of data governance and compliance frameworks is crucial.

North Highland values a people-first approach, emphasizing collaboration, mentorship, and continuous growth. This guide will equip you with the specific insights and knowledge needed to excel in your interview and demonstrate your alignment with North Highland's mission.

The interview process for a Data Engineer role at North Highland 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 alignment with the company's values.

1. Initial Phone Screening

The process begins with an initial phone screening, usually lasting about 30 to 60 minutes. This call is typically conducted by a recruiter or HR representative who will discuss your background, the role, and the company culture. Expect to answer questions about your experience, skills, and what you are looking for in your next position. This is also an opportunity for you to ask questions about the company and the role.

2. Technical Assessment

If you pass the initial screening, you will be invited to a technical assessment. This may take place over a video call and can include a mix of technical questions and practical exercises. Candidates might be asked to solve problems related to data architecture, data modeling, or ETL processes. You may also be required to demonstrate your proficiency in relevant programming languages and tools, such as SQL, Python, or cloud services like GCP, AWS, or Azure.

3. Case Study or Process Modeling Exercise

Following the technical assessment, candidates often participate in a case study or process modeling exercise. This step is designed to evaluate your analytical thinking and problem-solving skills. You may be presented with a real-world scenario and asked to design a data pipeline or create a process model. This exercise typically lasts around 30 to 90 minutes and may involve collaboration with other team members or interviewers.

4. In-Person or Final Interview

The final stage usually consists of one or more in-person interviews, which may include meetings with senior management or team leads. These interviews are more conversational and focus on your past experiences, how you handle challenges, and your approach to teamwork and leadership. Expect to discuss your technical expertise in greater detail and how it aligns with the company's goals and projects.

5. Feedback and Offer

After the final interviews, candidates can expect to receive feedback on their performance. If successful, you will receive a job offer, which may include discussions about salary, benefits, and other employment terms. The company emphasizes a people-first culture, so expect a thorough explanation of how your role fits into the broader organizational landscape.

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

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

Understand the Company Culture

North Highland prides itself on being a people-first organization that values collaboration and individual growth. Familiarize yourself with their core values and how they translate into daily operations. Be prepared to discuss how your personal values align with theirs, and demonstrate your commitment to fostering a positive team environment. Highlight experiences where you have contributed to a collaborative culture or helped others grow.

Prepare for Technical Assessments

Given the technical nature of the Data Engineer role, you should be ready for hands-on assessments that may include designing data pipelines, optimizing data models, or implementing ETL processes. Brush up on your knowledge of cloud platforms like GCP, AWS, or Azure, and be prepared to discuss your experience with big data technologies such as Hadoop and Spark. Practice articulating your thought process while solving technical problems, as interviewers may be interested in your approach as much as the final solution.

Emphasize Communication Skills

North Highland values effective communication, especially in a consultancy role where you will need to collaborate with various stakeholders. Be prepared to discuss how you have successfully communicated complex technical concepts to non-technical audiences. Share examples of how you have worked with cross-functional teams to achieve project goals, and highlight your ability to mentor others.

Be Ready for Behavioral Questions

Expect a mix of behavioral and situational questions that assess your problem-solving abilities and how you handle challenges. Use the STAR (Situation, Task, Action, Result) method to structure your responses. Reflect on past experiences where you faced obstacles in data engineering projects and how you overcame them. This will demonstrate your resilience and adaptability, qualities that North Highland values in its employees.

Showcase Your Passion for Change

As a consultancy focused on transformation, North Highland seeks candidates who are passionate about making a difference. Be prepared to discuss your motivation for joining the company and how you envision contributing to their mission of driving change. Share specific examples of how you have initiated or contributed to change in previous roles, whether through process improvements, innovative solutions, or team leadership.

Follow Up Thoughtfully

After your interview, send a personalized thank-you note to your interviewers. Mention specific topics discussed during the interview that resonated with you, and reiterate your enthusiasm for the role and the company. This not only shows your appreciation but also reinforces your interest in the position and helps you stand out in their minds.

By following these tips, you can present yourself as a well-rounded candidate who is not only technically proficient but also a great cultural fit for North Highland. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at North Highland. The interview process will likely assess your technical skills, problem-solving abilities, and how well you can communicate complex ideas. Be prepared to discuss your experience with data architecture, cloud platforms, and data processing technologies, as well as your approach to collaboration and leadership.

Technical Skills

1. Can you explain the differences between ETL and ELT processes?

Understanding the nuances between ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) is crucial for a Data Engineer, especially in cloud environments.

How to Answer

Discuss the definitions of both processes, emphasizing when to use each based on data volume, processing speed, and system architecture.

Example

“ETL is typically used when data needs to be transformed before loading into the target system, which is common in traditional data warehousing. ELT, on the other hand, allows for loading raw data into the target system first, which is more efficient for big data environments where transformation can occur post-load, leveraging the power of cloud computing.”

2. Describe your experience with cloud platforms like GCP, AWS, or Azure.

Your familiarity with cloud services is essential for this role, as North Highland emphasizes cloud-based solutions.

How to Answer

Highlight specific projects where you utilized cloud services, detailing the tools and technologies you employed.

Example

“I have extensive experience with GCP, particularly with BigQuery for data warehousing and Dataflow for stream processing. In my last project, I designed a data pipeline that ingested real-time data from various sources, processed it using Dataflow, and stored it in BigQuery for analytics, which significantly improved our reporting speed.”

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

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

How to Answer

Discuss specific techniques you use to validate and monitor data quality throughout the data pipeline.

Example

“I implement data validation checks at various stages of the pipeline, such as schema validation and data type checks. Additionally, I use monitoring tools to track data quality metrics and set up alerts for any anomalies, ensuring that any issues are addressed promptly.”

4. Can you walk us through a data modeling project you’ve worked on?

This question assesses your practical experience with data modeling, which is a key responsibility in the role.

How to Answer

Provide a detailed overview of a specific project, including the objectives, challenges, and outcomes.

Example

“In a recent project, I was tasked with designing a data model for a retail client. I started by gathering requirements from stakeholders, then created an ER diagram to visualize relationships. After implementing the model in a SQL database, I optimized it for performance, which resulted in a 30% reduction in query times.”

5. What tools do you use for workflow orchestration?

Familiarity with orchestration tools is important for managing complex data workflows.

How to Answer

Mention specific tools you have experience with and how you have used them in past projects.

Example

“I primarily use Apache Airflow for workflow orchestration. In my last role, I set up Airflow to automate ETL processes, allowing for better scheduling and monitoring of tasks. This not only improved efficiency but also provided clear visibility into the data pipeline’s performance.”

Problem-Solving and Case Studies

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

This question evaluates your problem-solving skills and your ability to think critically about data architecture.

How to Answer

Outline your approach step-by-step, from requirements gathering to implementation.

Example

“I would start by collaborating with stakeholders to understand their data needs and objectives. Next, I would design the architecture, selecting appropriate tools and technologies. After that, I would implement the pipeline, ensuring to include data validation and monitoring. Finally, I would conduct testing and gather feedback for any necessary adjustments.”

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

This question assesses your ability to handle difficulties and your resilience in problem-solving.

How to Answer

Share a specific example, focusing on the problem, your approach, and the outcome.

Example

“In a previous project, we faced performance issues with our data pipeline due to high data volume. I analyzed the bottlenecks and discovered that our transformation logic was inefficient. I refactored the code to optimize the transformations and implemented partitioning in our data storage, which improved processing time by over 50%.”

3. 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

Discuss the resources you use to keep your skills current, such as online courses, blogs, or community involvement.

Example

“I regularly follow industry blogs and participate in online forums like Stack Overflow and Reddit. I also take online courses on platforms like Coursera and attend webinars to learn about new tools and best practices. Networking with other professionals at meetups also helps me stay informed about emerging trends.”

4. Can you explain a time when you had to collaborate with data scientists or analysts?

Collaboration is key in data engineering, and this question assesses your teamwork skills.

How to Answer

Provide an example that highlights your ability to work cross-functionally and communicate effectively.

Example

“In a project where we were developing a machine learning model, I collaborated closely with data scientists to ensure they had access to clean and structured data. I set up a data pipeline that provided them with the necessary datasets, and we held regular meetings to discuss any adjustments needed, which ultimately led to a successful model deployment.”

5. What strategies do you use to communicate technical concepts to non-technical stakeholders?

Effective communication is essential, especially in a consultancy environment.

How to Answer

Discuss your approach to simplifying complex ideas and ensuring understanding.

Example

“I focus on using analogies and visual aids to explain technical concepts. For instance, when discussing data architecture, I might compare it to building a house, where each layer serves a specific purpose. I also encourage questions and provide examples relevant to their business context to ensure clarity.”