Cummins Inc. Data Engineer Interview Questions + Guide in 2025

Cummins Inc. is a global leader in power solutions and technology, committed to innovation and sustainability in everything they do.

The Data Engineer role at Cummins requires a collaborative mindset to work closely with operations and business stakeholders as well as IT partners to establish robust data pipelines that extract and transform vital information from various site systems like ERPs, WMSs, MESs, and SCADA. Key responsibilities include designing and automating data ingestion systems, monitoring data quality, implementing data governance processes, and developing scalable data pipelines using ETL/ELT tools. A successful candidate should possess strong SQL skills, familiarity with data modeling tools like Palantir, and experience in both IT and operational environments. Additionally, a solid understanding of data management infrastructure, programming skills in relevant languages, and an ability to communicate effectively across diverse teams are essential for this role.

This guide is crafted to equip you with the insights and preparation needed to excel in your interview for the Data Engineer position at Cummins. By understanding the role and its expectations, you will be better prepared to showcase your skills and fit for the company.

The interview process for a Data Engineer at Cummins Inc. is structured to assess both technical and interpersonal skills, ensuring candidates are well-rounded and fit for the collaborative environment. The process typically unfolds in several stages:

1. Initial Screening

The first step involves a phone interview with a recruiter or HR representative. This conversation usually lasts around 30 minutes and focuses on your resume, general qualifications, and interest in the role. Expect to discuss your background, relevant experiences, and motivations for applying to Cummins. This is also an opportunity for you to ask questions about the company culture and the specifics of the Data Engineer role.

2. Technical Assessment

Following the initial screening, candidates may be required to complete a technical assessment. This could include online tests that evaluate your skills in SQL, data extraction, and programming. The assessment is designed to gauge your technical proficiency and problem-solving abilities, particularly in areas relevant to data engineering tasks such as ETL processes and data quality monitoring.

3. Panel Interviews

Candidates who pass the technical assessment will typically participate in a panel interview. This stage often consists of multiple interviewers, including technical leads and team members. The panel will ask a mix of behavioral and technical questions, focusing on your experience with data pipelines, system design, and collaboration with stakeholders. Expect to discuss past projects, your approach to data governance, and how you handle data quality issues.

4. Final Interview

The final interview is usually conducted with a hiring manager or senior leadership. This round may involve deeper discussions about your long-term career goals, your understanding of the data engineering landscape, and how you can contribute to Cummins' objectives. You may also be asked to present a case study or a project that showcases your skills in data modeling and pipeline optimization.

Throughout the interview process, candidates are encouraged to demonstrate their problem-solving skills, ability to work in a team, and effective communication. The emphasis on collaboration and customer focus is crucial, as Cummins values diverse perspectives and teamwork.

As you prepare for your interview, consider the types of questions that may arise in each of these stages, particularly those that relate to your technical expertise and past experiences.

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

Understand the Role and Its Impact

Before your interview, take the time to deeply understand the responsibilities of a Data Engineer at Cummins. Familiarize yourself with how this role contributes to the overall success of the company, particularly in establishing robust data pipelines and ensuring data quality. Be prepared to discuss how your skills and experiences align with these responsibilities and how you can add value to the team.

Prepare for Behavioral Questions

Expect a significant focus on behavioral questions during your interview. Reflect on your past experiences and be ready to share specific examples that demonstrate your problem-solving abilities, teamwork, and adaptability. Given the emphasis on collaboration and customer focus at Cummins, think about instances where you successfully worked with diverse teams or stakeholders to achieve a common goal.

Brush Up on Technical Skills

Given the technical nature of the role, ensure you are well-versed in SQL and data extraction techniques. Be prepared to discuss your experience with ETL processes and any relevant tools you have used. Additionally, familiarize yourself with data modeling concepts and be ready to explain how you would approach designing and optimizing data pipelines. If you have experience with cloud-based platforms or big data technologies, be sure to highlight that as well.

Emphasize Collaboration and Communication

Cummins values collaboration and effective communication. Be prepared to discuss how you have built partnerships in previous roles and how you approach working with cross-functional teams. Highlight your ability to communicate complex technical concepts to non-technical stakeholders, as this will be crucial in ensuring successful project outcomes.

Show Your Interest in Continuous Improvement

Demonstrate your commitment to continuous improvement and innovation. Discuss any experiences you have had with process optimization or automation in your previous roles. Be ready to share ideas on how you could contribute to enhancing data management practices at Cummins, particularly in terms of data quality monitoring and governance.

Be Ready for Scenario-Based Questions

You may encounter scenario-based questions that assess your problem-solving skills and decision-making abilities. Prepare to think critically about how you would handle specific challenges related to data quality or pipeline optimization. Use the STAR (Situation, Task, Action, Result) method to structure your responses effectively.

Research Company Culture

Understanding Cummins' company culture is essential. They emphasize diversity, inclusion, and respect for different perspectives. Be prepared to discuss how you value diversity in the workplace and how you have contributed to fostering an inclusive environment in your previous roles.

Follow Up with Questions

At the end of your interview, be ready to ask insightful questions that demonstrate your interest in the role and the company. Inquire about the team dynamics, ongoing projects, or how the company measures success in data engineering. This not only shows your enthusiasm but also helps you gauge if Cummins is the right fit for you.

By following these tips and preparing thoroughly, you will position yourself as a strong candidate for the Data Engineer role at Cummins. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Cummins Inc. The interview process will likely focus on your technical skills, problem-solving abilities, and your capacity to work collaboratively with various stakeholders. Be prepared to discuss your experience with data pipelines, SQL, and data quality, as well as your approach to system design and automation.

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 the backbone of data integration and management.

How to Answer

Discuss the steps involved in ETL, emphasizing how each step contributes to the overall data pipeline and the importance of data quality and integrity.

Example

“ETL is a critical process in data engineering that involves extracting data from various sources, transforming it into a suitable format, and loading it into a target database. This process ensures that data is accurate, consistent, and ready for analysis, which is essential for making informed business decisions.”

2. How do you ensure data quality in your data 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 monitor and validate data quality, such as automated testing, data profiling, and implementing data governance practices.

Example

“I implement data quality checks at various stages of the data pipeline, including validation rules during the ETL process and regular audits of the data. Additionally, I use automated monitoring tools to alert me to any anomalies, ensuring that any issues are addressed promptly.”

3. Describe your experience with SQL and how you use it in data engineering.

SQL is a fundamental skill for Data Engineers, and your proficiency will be assessed.

How to Answer

Highlight your experience with SQL, including specific tasks you have performed, such as writing complex queries, optimizing performance, and working with different database systems.

Example

“I have extensive experience using SQL for data extraction and transformation. I often write complex queries to join multiple tables and aggregate data for reporting purposes. Additionally, I focus on optimizing query performance by indexing and analyzing execution plans.”

4. What is your approach to designing a data pipeline?

Designing an efficient data pipeline is a key responsibility of a Data Engineer.

How to Answer

Outline your process for designing a data pipeline, including considerations for scalability, reliability, and performance.

Example

“When designing a data pipeline, I start by understanding the data sources and the requirements of the end-users. I then choose the appropriate ETL tools and design the architecture to ensure scalability and reliability. I also incorporate monitoring mechanisms to track performance and data quality throughout the pipeline.”

5. Can you explain the concept of data governance and its significance?

Data governance is essential for managing data integrity and compliance.

How to Answer

Discuss the principles of data governance and how they apply to data engineering, including data stewardship, compliance, and data lifecycle management.

Example

“Data governance involves establishing policies and standards for managing data throughout its lifecycle. It is significant because it ensures data integrity, compliance with regulations, and accountability within the organization. I actively participate in data governance initiatives to promote best practices in data management.”

Behavioral Questions

1. Describe a time when you had to collaborate with a cross-functional team.

Collaboration is key in a Data Engineer role, especially when working with stakeholders from different departments.

How to Answer

Provide a specific example that highlights your teamwork skills, communication, and ability to achieve shared goals.

Example

“In my previous role, I collaborated with the IT and operations teams to implement a new data pipeline. I facilitated regular meetings to ensure everyone was aligned on the project goals and timelines. This collaboration led to a successful implementation that improved data accessibility for the entire organization.”

2. How do you handle conflicts within a team?

Conflict resolution skills are important for maintaining a productive work environment.

How to Answer

Discuss your approach to resolving conflicts, emphasizing communication, empathy, and finding common ground.

Example

“When conflicts arise, I believe in addressing them directly and openly. I listen to all parties involved to understand their perspectives and work towards a solution that satisfies everyone. For instance, during a project, I mediated a disagreement between team members about the data model design, which ultimately led to a more robust solution.”

3. Where do you see yourself in five years?

This question assesses your career aspirations and alignment with the company’s goals.

How to Answer

Share your professional goals and how they relate to the role and the company’s mission.

Example

“In five years, I see myself as a senior data engineer, leading projects that drive data-driven decision-making within the organization. I aim to deepen my expertise in cloud technologies and data governance, contributing to Cummins’ commitment to innovation and excellence in data management.”

4. Can you give an example of a challenging problem you solved?

Problem-solving is a critical skill for Data Engineers, and interviewers will want to hear about your experiences.

How to Answer

Describe a specific challenge you faced, the steps you took to resolve it, and the outcome.

Example

“I once encountered a significant data quality issue where discrepancies were found in the sales data. I conducted a root cause analysis, identified the source of the errors in the data entry process, and implemented a new validation protocol that reduced errors by 30%. This not only improved data quality but also increased trust in our reporting.”

5. Why are you interested in working for Cummins?

This question assesses your motivation and fit for the company culture.

How to Answer

Express your enthusiasm for the company’s mission, values, and the specific role you are applying for.

Example

“I am drawn to Cummins because of its commitment to innovation and sustainability. I admire how the company leverages data to drive operational efficiency and improve customer experiences. I believe my skills in data engineering align well with Cummins’ goals, and I am excited about the opportunity to contribute to such impactful projects.”