Conagra Foods Data Engineer Interview Questions + Guide in 2025

Conagra Foods is a leading North American branded food company known for its commitment to innovation and quality in the food industry.

As a Data Engineer at Conagra, you will play a crucial role in building and maintaining the Enterprise Data Platform, utilizing cutting-edge technologies like Databricks, Snowflake, and Palantir. Your primary responsibilities will include developing and optimizing data pipelines to integrate data from diverse sources, ensuring the accuracy and reliability of data for business insights. You will work closely with cross-functional teams, including data scientists and analysts, to understand their data needs and provide solutions that drive data-driven decision-making. A strong proficiency in SQL is essential, as you'll be tasked with writing complex queries and data transformations to support various business use cases. Furthermore, your ability to automate workflows will enhance processing efficiency and reduce manual effort across the organization. Given the collaborative nature of the role, excellent communication skills and a strong problem-solving mindset are essential traits that will help you thrive in Conagra's dynamic environment.

This guide will help you prepare for your job interview by providing insights into the expectations and key competencies required for the Data Engineer role at Conagra Foods, enabling you to present yourself as a well-rounded and qualified candidate.

The interview process for a Data Engineer at Conagra Foods is designed to assess both technical skills and cultural fit within the organization. It typically consists of several structured rounds, each focusing on different aspects of the candidate's qualifications and experiences.

1. Initial Screening

The first step in the interview process is an initial screening, which usually takes place via a video call with a recruiter. This conversation lasts about 30 minutes and serves to gauge your interest in the role, discuss your background, and evaluate your alignment with Conagra's values and culture. The recruiter will ask about your previous work experiences, particularly those related to data engineering, and your motivation for applying to Conagra.

2. Technical Interview

Following the initial screening, candidates typically participate in a technical interview. This round is often conducted via video conferencing and focuses on assessing your technical expertise in SQL, data modeling, and data pipeline development. You may be asked to solve coding problems or discuss your experience with cloud-based technologies like Databricks and Snowflake. Expect to demonstrate your understanding of data transformation processes and your ability to optimize SQL queries.

3. Group Interview

The next stage often involves a group interview with several members of the data engineering team and management. This format allows interviewers to evaluate your collaborative skills and how you interact with potential colleagues. Questions may revolve around your previous project challenges, teamwork experiences, and how you handle feedback. This round also provides an opportunity for you to ask questions about the team dynamics and the projects you would be involved in.

4. Onsite Interview

The final stage is typically an onsite interview, which may include a tour of the office and meetings with various team members. During this round, you will engage in multiple one-on-one interviews that cover both technical and behavioral aspects. Interviewers will delve deeper into your problem-solving abilities, your experience with data governance, and your approach to automating workflows. You may also be asked to present a past project or case study that highlights your skills and contributions.

As you prepare for these interviews, it's essential to reflect on your experiences and be ready to discuss specific examples that demonstrate your technical capabilities and teamwork skills.

Next, let's explore the types of questions you might encounter during the interview process.

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

Emphasize Collaboration and Teamwork

Conagra Foods values a collaborative work environment, as evidenced by the group interview experiences shared by candidates. Be prepared to discuss your previous experiences working in teams, particularly how you contributed to project success and navigated challenges. Highlight your ability to communicate effectively with cross-functional teams, including data scientists and business analysts, to ensure that data requirements are met.

Showcase Your Technical Proficiency

Given the emphasis on SQL and data pipeline development in the role, ensure you are well-versed in writing complex SQL queries and optimizing them for performance. Be ready to discuss specific projects where you utilized SQL, Databricks, or Snowflake to solve data challenges. Additionally, if you have experience with Python or PySpark, be prepared to share examples of how you used these tools for data processing and transformation.

Prepare for Behavioral Questions

Expect behavioral questions that assess your problem-solving skills and ability to handle challenges. Use the STAR (Situation, Task, Action, Result) method to structure your responses. For instance, you might be asked about a time you improved a data process or resolved a data quality issue. Reflect on your past experiences and prepare concise, impactful stories that demonstrate your skills and contributions.

Understand the Company Culture

Conagra Foods prides itself on having an energized and inclusive culture. Familiarize yourself with the company's values and mission, and think about how your personal values align with theirs. During the interview, express your enthusiasm for contributing to a culture that prioritizes innovation and collaboration. This will help you connect with your interviewers on a personal level.

Be Ready to Discuss Data Governance

As data governance is a critical aspect of the role, be prepared to discuss your understanding of data governance principles and how you have implemented them in previous roles. Share examples of how you ensured data accuracy, reliability, and compliance with privacy standards. This will demonstrate your commitment to maintaining high data quality and integrity.

Ask Insightful Questions

Prepare thoughtful questions to ask your interviewers about the team dynamics, ongoing projects, and the technologies they are currently using. This not only shows your genuine interest in the role but also gives you valuable insights into the work environment and expectations. Questions about how the team collaborates on data initiatives or how they measure success can lead to meaningful discussions.

By following these tips and tailoring your responses to reflect your experiences and alignment with Conagra Foods' values, you'll position yourself as a strong candidate for the Data Engineer role. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Conagra Foods. The interview process will likely focus on your technical skills, problem-solving abilities, and experience working collaboratively within teams. Be prepared to discuss your past projects, the technologies you've used, and how you've contributed to data-driven solutions.

Technical Skills

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

This question assesses your proficiency in SQL, which is crucial for data transformation and analysis.

How to Answer

Discuss specific projects where you utilized SQL, focusing on the complexity of the queries you wrote and the outcomes they achieved.

Example

“In my previous role, I developed complex SQL queries to extract and transform data from multiple sources for reporting purposes. One notable project involved optimizing a query that reduced processing time by 30%, which significantly improved our reporting efficiency.”

2. What ETL tools have you used, and can you describe a project where you implemented an ETL process?

This question evaluates your familiarity with ETL tools and your practical experience in data integration.

How to Answer

Mention the ETL tools you have experience with and provide a detailed example of an ETL process you designed or improved.

Example

“I have worked extensively with Informatica and Talend. In one project, I designed an ETL process that integrated data from various sources into our data warehouse, ensuring data quality and consistency. This process automated data loading, which reduced manual effort and errors.”

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

This question focuses on your approach to maintaining high data quality standards.

How to Answer

Explain the methods and tools you use to validate data and ensure its accuracy throughout the data lifecycle.

Example

“I implement automated data validation checks at various stages of the data pipeline. For instance, I use unit tests to verify data transformations and monitor data quality metrics to catch any anomalies early in the process.”

4. Can you explain your experience with cloud-based data platforms like Snowflake or Databricks?

This question assesses your knowledge of modern data platforms that Conagra uses.

How to Answer

Discuss your experience with these platforms, including specific features you utilized and the benefits they provided.

Example

“I have worked with Snowflake for data warehousing and found its scalability and performance to be exceptional. I used it to create a data model that supported real-time analytics, which allowed our business teams to make quicker decisions based on up-to-date information.”

5. Describe a time when you optimized a data pipeline. What steps did you take?

This question evaluates your problem-solving skills and ability to improve existing processes.

How to Answer

Provide a specific example of a data pipeline you optimized, detailing the challenges you faced and the solutions you implemented.

Example

“I identified a bottleneck in our data pipeline that was causing delays in data availability. I analyzed the query performance and implemented indexing strategies, which improved the data load time by 40%. This optimization allowed our analytics team to access data much faster.”

Collaboration and Teamwork

1. How do you approach gathering data requirements from stakeholders?

This question assesses your communication skills and ability to work with cross-functional teams.

How to Answer

Describe your process for engaging with stakeholders to understand their data needs and how you translate those into technical requirements.

Example

“I typically start by conducting interviews with stakeholders to understand their specific needs. I then document these requirements and create a data model that aligns with their expectations, ensuring that I maintain open communication throughout the process.”

2. Can you provide an example of a challenging project you worked on with a team?

This question evaluates your teamwork and conflict resolution skills.

How to Answer

Share a specific project where you faced challenges and how you collaborated with your team to overcome them.

Example

“During a project to integrate a new data source, we faced conflicting priorities among team members. I facilitated a meeting to align our goals and responsibilities, which helped us work more effectively together and ultimately meet our project deadline.”

3. What strategies do you use to mentor junior engineers?

This question assesses your leadership and mentoring abilities.

How to Answer

Discuss your approach to mentoring, including any specific techniques or practices you find effective.

Example

“I believe in hands-on mentoring, so I often pair program with junior engineers on complex tasks. I also encourage them to take ownership of smaller projects, providing guidance and feedback along the way to help them grow their skills.”

4. How do you handle feedback from team members or stakeholders?

This question evaluates your receptiveness to feedback and ability to adapt.

How to Answer

Explain how you view feedback as an opportunity for growth and how you incorporate it into your work.

Example

“I welcome feedback as it helps me improve my work. For instance, after receiving input on a data model I designed, I made adjustments that enhanced its usability for the analytics team. I always strive to create an environment where team members feel comfortable sharing their thoughts.”

5. Describe a time when you had to communicate complex technical information to a non-technical audience.

This question assesses your ability to bridge the gap between technical and non-technical stakeholders.

How to Answer

Provide an example of how you simplified complex concepts for a non-technical audience.

Example

“I once presented a data integration project to a group of marketing professionals. I used visual aids and analogies to explain the data flow and its impact on their campaigns, which helped them understand the value of the project and how it would benefit their work.”