Data Engineering Manager Interview Questions

Interviews for data engineering managers assess two important skills:

• Technical expertise
• Leadership skills

First and foremost, data engineering managers must be talented engineers, but that isn’t sufficient on its own to manage a team. They must also be strong leaders that can direct a team of engineers to produce results by inspiring or incentivizing their colleagues.

Due to the need for both of these skills, the interview will therefore be a mix of technical questions and behavioral approaches, focusing on a candidate’s people leadership and engineering management experience.

Data engineering managers are responsible for:

• Team Leadership – Engineering managers are responsible for recruiting and developing a team, assigning tasks, and driving performance.
• Setting Goals – Engineering managers steer the direction of the department and define the output. They set KPIs, develop a roadmap, and track progress.
• Stakeholder Communication – Managers must be adept at communicating and collaborating cross-functionally. The manager should steer the output of the department to meet the strategic goals of the larger organization.
• Project management – Data engineer managers set budgets and allocate resources to ensure projects are completed on time. They are also able to identify opportunities to increase efficiency and reduce costs.

Interviews for data engineer manager roles typically include 2-3 rounds of behavioral and leadership questions. These rounds will represent the day-to-day responsibilities of a data engineering manager.

In addition, these interviews typically include 1-2 technical rounds, which are geared towards system design case studies but may include SQL, system design, and/or machine learning questions. We will include technical questions to expect below, but you can also check out data engineering interview questions.

The process for management interviews is standard across the industry. They involve a short recruiter call, followed by a hiring manager screen and technical screen. If you pass this initial screening process, you’ll be invited to an on-site interview.

On-site interviews for data engineer management roles typically include 5 rounds, including:

• Behavioral Rounds – These questions primarily focus on your accomplishments, how you measure your impact, and on-the-job challenges you’ve addressed in previous roles.
• Leadership Rounds – You will face broad discussion-based questions that assess leadership style, such as how you manage a team at the tactical level, your ability to mentor and develop teams, and how you approach technical project management.
• Technical Rounds – You might expect 1-2 technical rounds, focusing on data engineering case study questions. These are typically scenario-based problems that require candidates to develop a solution and walk interviewers through their process.

Behavioral interviews are discussion-based and assess leadership and management philosophies. The interviewer will want to see how you approach and address different types of real-world scenarios. These questions are closely linked to your future responsibilities:

• Leadership – Leadership questions assess your ability to lead a team, as well as to create a strategic vision. These questions typically explore past projects, your team leadership philosophy, and your approach to hypothetical situations.

Example: Describe a time when you had to lead your team through a challenging data engineering project. How did you ensure everyone was aligned and motivated to accomplish the project goals?

• Communication – Behavioral questions in data engineer manager interviews assess your ability to motivate and inspire a team, gather information, and relay technical requirements to team members and non-technical stakeholders.

Example: Explain a situation where you had to communicate complex data engineering concepts to non-technical stakeholders. How did you ensure they understood the importance and implications of the project?

• Problem Solving – These questions assess how you have solved problems on the job or your approach to hypothetical problems. They may include questions about accomplishing goals with limited time or resources, how you develop and inspire a team, or how you have handled letting employees go when there isn’t a good fit.

Example: Describe a data engineering project where you faced significant constraints, such as limited resources or a tight deadline. How did you overcome these challenges and deliver a successful outcome?

• Product Sense – The best management candidate understands how to steer the direction of the engineering department to help the company reach strategic goals. These questions cover past projects or may take the form of traditional engineering product case study questions.

Example: Walk us through a past data engineering project where you had to align your team’s efforts with the company’s strategic goals. How did you ensure that your team’s work contributed to the overall success of the organization?

One tip: Be selective about the experiences you choose to describe. Your answers should illustrate your management experience and skills. For example, describing a disagreement over strategic direction rather than a simple coding dispute would be a more appropriate response to the question above.

You should also use a simple framework to structure your response. With an approach like STAR, you would:

• Describe the situationyou were in.
• Define the task you needed to complete.
• Outline the actions you took.
• Detail the results you achieved.

Sample Question:

Describe a complex data engineering project you worked on. What were the biggest challenges you faced?

Answer:

In a previous role, I managed a team that had been tasked with building a real-time streaming data processing system to support a high-traffic web application. The biggest challenge we faced was building a system that could handle the high volume of data, while also maintaining low latency. To overcome this, we implemented a microservices architecture and used Apache Kafka as the messaging system. We also had to ensure the system was scalable and fault-tolerant, so we implemented redundancy and monitoring mechanisms to detect issues and quickly recover from them.

Sample Question:

How do you manage conflicting priorities and stakeholder expectations when working on multiple projects?

Answer:

When working on multiple projects, I prioritize based on the impact each project has on the business and the resources available. I work closely with stakeholders to understand their needs and expectations, then set realistic timelines and milestones. If conflicts arise, I communicate openly and transparently with all stakeholders to ensure that everyone is aware of the situation.

More Behavioral Questions:

• Describe a time when you failed on a project. How did you respond?
• Why are you interested in the position? Why are you leaving your current position?
• Tell me about a time when you had to work with a difficult stakeholder to complete a project. How did you handle the situation?
• Can you give an example of a particularly challenging data engineering problem you encountered and how you approached solving it?
• Tell me about a time when you had to lead a team through a significant change or transition. What was your approach and what were the results?
• Can you describe a time when you had to make a tough decision that impacted your team? How did you communicate the decision and what was the outcome?
• Describe a time when you had to deal with a technical issue in production. How did you address the issue and what steps did you take to prevent it from happening again in the future?

Click on the link for more behavioral data science questions at Interview Query.

Question:

Describe a time when you had to motivate your team to achieve a challenging goal. What steps did you take to build morale and ensure your team was successful?

Answer:

As a data engineering manager at my previous company, I lead a team to migrate our data warehouse to a new platform within a tight timeline. To motivate my team, I first made sure they understood the importance of the project and how it would benefit the company. Then, I broke down the project into smaller, achievable milestones and created a detailed plan with clear deadlines for each milestone.

I also encouraged my team to collaborate and share ideas, and I made sure to recognize and reward their hard work and accomplishments along the way. Ultimately, by breaking the project down into smaller pieces, providing regular feedback and recognition, and fostering a positive team culture, we were able to successfully complete the full migration on time.

Question:

How do you prioritize technical debt and ensure that it doesn’t negatively impact your team’s ability to deliver new features and projects?

Answer:

I prioritize technical debt by working closely with my team to identify areas of the codebase that require attention. I encourage my team to be proactive about addressing technical debt, and we regularly set aside time to tackle these issues.

To ensure that technical debt doesn’t negatively impact our ability to deliver new features and projects, I also work to balance these efforts with our other priorities. I prioritize high-impact technical debt items and schedule them alongside new feature development. I also regularly assess and re-prioritize our backlog of technical debt items to ensure that we are addressing the most critical items first.

More Example Leadership Questions

• How would you define your leadership style? Can you give an example of a time when you used this style to effectively lead a team?
• Tell me about a time when you had to make a tough decision as a leader. How did you approach the decision-making process, and what was the outcome?
• Can you describe a time when you had to coach or mentor a team member to improve their performance? What was your approach, and what were the results?
• How do you ensure that your team is staying up to date with the latest data engineering trends and technologies? Can you give an example of a time when you implemented a new technology or process that improved your team’s performance?
• Describe a time when you had to delegate a task or project to a team member. How did you select the person for the task, and what steps did you take to ensure their success?
• How do you build and maintain strong relationships with stakeholders, both within and outside of your organization? Can you give an example of a time when you successfully managed stakeholder expectations?
• When managing a team of developers, how do you delegate work to each team member?

In management interviews, you can expect medium-to-hard technical questions. During the technical screening, these might include smaller case studies or ETL SQL questions. During an on-site, the technical questions are generally a multi-step data engineering case study.

There’s a way to approach technical questions, and our data engineering learning path provides frameworks for all of the types of questions you’re most likely to face.

Question:

Let’s say that you’re in charge of getting payment data into your internal data warehouse. How would you build an ETL pipeline to get Stripe payment data into the database so analysts can build revenue dashboards and run analytics?

Answer:

See a mock interview answer for this question.

Question:

You’re in charge of designing the end-to-end architecture of an e-commerce platform like Amazon. What clarifying questions would you ask? What kind of end-to-end architecture would you design for this company (both for ETL and reporting)?

More context: Let’s say you work for an e-commerce company. Vendors can send products to the company’s warehouse to be listed on the website.

Users can order any in-stock products and submit returns for refunds if they’re not satisfied. The front end of the website includes a vendor portal that provides sales data in daily, weekly, monthly, quarterly, and yearly intervals.

Answer:

See a mock interview answer for this question.

If you’d like more practice, check out more data engineering interview questions at Interview Query.

For data engineering manager candidates, here are some unique tips to help you succeed in your interviews:

• Emphasize your fit with the company culture: As a data engineering manager, you’ll be responsible for defining and maintaining the team’s culture. Demonstrate that you share the organization’s values and can personally align yourself or a future team with its mission. You can achieve this by matching the energy in the room, highlighting your core principles, and sharing insights into your personality and character.
• Build a rapport with the recruiter: Recruiters can be a valuable ally in securing a managerial position. Connect with them, ask questions, and request feedback on your application. This way, you can gain a better understanding of the role and tailor your interview responses accordingly.
• Practice, practice, practice: You can never over-prepare for an interview. Conduct as many mock interviews as possible, record yourself, and analyze your responses. This will help you identify areas where you need to improve and fine-tune your storytelling skills.
• Know the company’s tech: Researching the company’s business model and internal structures is vital for a successful interview. It demonstrates your interest in the company and provides you with the necessary knowledge to answer engineering case study questions confidently.
• Show your interest: Demonstrate your genuine interest in the role and the company by asking thoughtful questions that showcase your passion for data engineering. This helps to establish a rapport with the interviewer and conveys your commitment to contributing meaningfully to the team.

Before any data engineering interview, explore our data engineering learning path. This multi-course path teaches best practices for answering technical and case study questions in data engineering interviews and will help you prepare and refine your interviewing skills.