Kiewit Data Analyst Interview Questions + Guide in 2025

Kiewit is a leading construction and engineering company known for improving and connecting communities through its large-scale projects across North America.

As a Data Analyst at Kiewit, you will play a pivotal role in leveraging data to address complex business challenges, particularly in the construction and engineering sectors. Key responsibilities include delivering efficient data engineering solutions that meet stakeholder needs, leading and mentoring a technical team, and acting as a trusted advisor for various departments within the organization. You will be expected to design and implement data analytics processes, using tools such as Python, SQL, and Azure platforms, to ensure high-quality data governance and enablement. Strong analytical, problem-solving, and communication skills are essential, along with a proactive approach to project execution and the ability to collaborate with diverse teams. This role embodies Kiewit’s commitment to data-driven decision-making and continuous improvement in operational excellence.

This guide will help you prepare effectively for your interview, equipping you with insights into the role and the expectations at Kiewit, ultimately enhancing your chances of success.

The interview process for a Data Analyst position at Kiewit is structured to assess both technical skills and cultural fit within the organization. Candidates can expect a multi-step process that includes initial screenings, technical assessments, and final interviews.

1. Initial Phone Screen

The first step typically involves a phone interview with a recruiter or HR representative. This conversation lasts about 30-45 minutes and focuses on your background, experience, and motivation for applying to Kiewit. The recruiter will also provide insights into the company culture and the specifics of the Data Analyst role. Be prepared to discuss your educational background, relevant work experience, and how your skills align with Kiewit's mission.

2. Technical Interview

Following the initial screen, candidates may be invited to a technical interview, which is often conducted via video chat. This session usually lasts around an hour and is led by a member of the data services team. During this interview, you will be asked to demonstrate your proficiency in data analysis tools and techniques, including SQL and Python. Expect to discuss your past projects, the methodologies you employed, and how you approached problem-solving in data-related tasks.

3. Behavioral Interview

The next step in the process is a behavioral interview, which may take place in person or via video. This round focuses on assessing your interpersonal skills, teamwork, and how you handle challenges in a work environment. Interviewers will likely ask about specific situations where you demonstrated leadership, collaboration, and conflict resolution. They may also inquire about your experience working with stakeholders and how you communicate complex data findings to non-technical audiences.

4. Final Interview

The final interview typically involves meeting with hiring managers and possibly other team members. This round is more in-depth and may include discussions about your long-term career goals, your fit within the team, and how you can contribute to Kiewit's data-driven initiatives. You may also be asked to present a case study or a project you have worked on, showcasing your analytical skills and ability to derive actionable insights from data.

5. Reference Check

After successfully completing the interview rounds, Kiewit may conduct a reference check to verify your previous work experience and performance. This step is crucial in ensuring that candidates align with the company's values and expectations.

As you prepare for your interview, consider the types of questions that may arise in each of these stages, particularly those that assess your technical expertise and your ability to work collaboratively in a team environment.

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

Understand the Company Culture

Kiewit values strong interpersonal skills and a collaborative work environment. Given the feedback from previous candidates, it’s essential to approach the interview with a positive attitude and demonstrate your ability to work well with others. Be prepared to discuss how you’ve successfully collaborated with teams in the past and how you can contribute to a positive workplace culture.

Prepare for Behavioral Questions

Expect questions that assess your problem-solving abilities and how you handle challenges. Given the emphasis on overcoming difficulties in past interviews, prepare specific examples that showcase your resilience and analytical skills. Use the STAR (Situation, Task, Action, Result) method to structure your responses, ensuring you clearly articulate your thought process and the impact of your actions.

Showcase Your Technical Skills

As a Data Analyst at Kiewit, proficiency in SQL, Python, and data visualization tools like Power BI is crucial. Be ready to discuss your experience with these technologies in detail. Consider preparing a portfolio of past projects or analyses that highlight your technical capabilities and how they’ve contributed to business outcomes. This will not only demonstrate your skills but also your ability to apply them in real-world scenarios.

Communicate Clearly and Confidently

Strong communication skills are vital for this role, especially when explaining complex data findings to non-technical stakeholders. Practice articulating your thoughts clearly and concisely. During the interview, focus on being direct and confident in your responses, while also being open to questions and feedback.

Be Ready for a Technical Assessment

While the interview process may include behavioral questions, be prepared for a technical assessment that tests your analytical skills. Brush up on your SQL querying abilities and be ready to solve problems on the spot. Familiarize yourself with common data analysis scenarios relevant to the construction and engineering sectors, as this will help you think critically during the assessment.

Demonstrate Your Business Acumen

Kiewit seeks candidates who understand the business implications of their work. Be prepared to discuss how your analytical solutions can drive business success. Think about how data can be leveraged to improve project outcomes, reduce costs, or enhance efficiency. This will show that you not only have the technical skills but also the strategic mindset to contribute to Kiewit’s goals.

Follow Up with Gratitude

After the interview, send a thank-you email to express your appreciation for the opportunity to interview. This is a chance to reiterate your enthusiasm for the role and the company. Mention specific points from the interview that resonated with you, which can help reinforce your interest and leave a positive impression.

By following these tips, you can position yourself as a strong candidate for the Data Analyst role at Kiewit. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Analyst interview at Kiewit. The interview process will likely focus on your technical skills, problem-solving abilities, and your capacity to communicate effectively with stakeholders. Be prepared to discuss your experience with data analysis, project management, and how you can leverage data to solve business problems.

Technical Skills

1. Can you describe your experience with SQL and how you have used it in past projects?

Understanding your SQL proficiency is crucial, as it is a key skill for data analysts at Kiewit.

How to Answer

Discuss specific projects where you utilized SQL to extract, manipulate, or analyze data. Highlight any complex queries you wrote and the impact of your work.

Example

“In my previous role, I used SQL to analyze sales data, writing complex queries to identify trends and generate reports for management. This analysis led to a 15% increase in sales by targeting underperforming regions.”

2. How do you approach data cleaning and preparation?

Data quality is essential for accurate analysis, and interviewers will want to know your methods.

How to Answer

Explain your process for identifying and correcting data issues, including any tools or techniques you use.

Example

“I typically start by assessing the data for missing values and inconsistencies. I use Python libraries like Pandas for data cleaning, ensuring that the dataset is accurate and ready for analysis. This step is crucial for maintaining the integrity of my findings.”

3. Describe a challenging data analysis project you worked on. What was your approach?

This question assesses your problem-solving skills and ability to handle complex tasks.

How to Answer

Outline the project, the challenges faced, and the steps you took to overcome them.

Example

“I worked on a project analyzing customer feedback data to improve service delivery. The challenge was the unstructured nature of the data. I used natural language processing techniques to categorize feedback, which helped the team implement targeted improvements.”

4. What data visualization tools have you used, and how do you decide which to use for a project?

Kiewit values effective communication of data insights, making this question relevant.

How to Answer

Discuss your experience with various visualization tools and your criteria for selecting one over another.

Example

“I have experience with Power BI and Tableau. I choose Power BI for its integration with Microsoft products when working with large datasets, while I prefer Tableau for its advanced visualization capabilities when presenting to stakeholders.”

5. How do you ensure that your analyses align with business objectives?

This question evaluates your understanding of the business context in your analyses.

How to Answer

Explain how you collaborate with stakeholders to understand their goals and how you tailor your analyses accordingly.

Example

“I regularly meet with project managers to discuss their objectives and challenges. By aligning my analyses with their goals, I ensure that my insights are actionable and relevant, ultimately driving better decision-making.”

Problem-Solving and Analytical Thinking

1. Describe a time when you had to analyze a large dataset. What tools did you use?

This question assesses your analytical skills and familiarity with data analysis tools.

How to Answer

Detail the dataset, the tools you used, and the insights you derived.

Example

“I analyzed a large dataset of project costs using Python and SQL. I utilized Pandas for data manipulation and Matplotlib for visualization, which helped identify cost overruns and led to a 10% reduction in future project budgets.”

2. How do you prioritize multiple projects with tight deadlines?

Kiewit values time management and the ability to handle pressure.

How to Answer

Discuss your strategies for prioritization and time management.

Example

“I use a combination of project management tools and techniques like the Eisenhower Matrix to prioritize tasks based on urgency and importance. This approach helps me focus on high-impact projects while ensuring timely delivery.”

3. Can you give an example of how you used data to influence a business decision?

This question evaluates your ability to translate data insights into actionable recommendations.

How to Answer

Share a specific instance where your analysis led to a significant business decision.

Example

“After analyzing customer retention data, I identified key factors contributing to churn. I presented my findings to the leadership team, which led to the implementation of a new customer loyalty program, resulting in a 20% increase in retention rates.”

4. How do you handle discrepancies in data?

This question assesses your attention to detail and problem-solving skills.

How to Answer

Explain your process for identifying and resolving data discrepancies.

Example

“When I encounter discrepancies, I first verify the data sources and check for errors in data entry. I then collaborate with relevant teams to understand the root cause and implement corrective measures to prevent future issues.”

5. What methods do you use to stay current with data analysis trends and technologies?

This question gauges your commitment to professional development.

How to Answer

Discuss your strategies for continuous learning and staying updated on industry trends.

Example

“I regularly attend webinars and workshops, follow industry leaders on social media, and participate in online courses. This helps me stay informed about the latest tools and techniques in data analysis.”