Corning Incorporated Data Analyst Interview Questions + Guide in 2025

Corning Incorporated is a leading innovator in materials science, committed to developing life-changing technologies that enhance the way the world interacts, works, learns, and lives.

The role of a Data Analyst at Corning is pivotal in leveraging data to drive informed decision-making across various business units. Key responsibilities include managing and interpreting data from diverse sources, ensuring data integrity, and providing analytical insights to support operational excellence. A successful Data Analyst will work closely with cross-functional teams, engaging in collaborative problem-solving and utilizing data visualization tools such as Power BI to create reports and dashboards that aid in strategic planning and execution. Required skills for this role encompass a strong foundation in statistics, SQL, and data analytics, alongside a high attention to detail and the ability to thrive in a dynamic, team-oriented environment. Additionally, familiarity with manufacturing processes and data management systems will set candidates apart, aligning with Corning's commitment to innovation and excellence.

This guide will equip you with the insights and preparation needed to articulate your experiences and skills effectively during the interview process, ultimately helping you to stand out as a candidate.

The interview process for a Data Analyst position at Corning Incorporated is structured to assess both technical skills and cultural fit within the organization. Candidates can expect a multi-step process that includes various interview formats and interactions with different team members.

1. Initial Screening

The process typically begins with an initial screening call conducted by a recruiter. This call lasts about 20-30 minutes and focuses on understanding the candidate's background, skills, and motivations for applying to Corning. The recruiter will also discuss the role's requirements and the company culture to gauge alignment.

2. Technical Assessment

Following the initial screening, candidates may be required to complete a technical assessment. This could involve a programming quiz or a take-home assignment that tests relevant skills such as SQL, data analysis, and familiarity with data visualization tools like PowerBI. The assessment is designed to evaluate the candidate's technical proficiency and problem-solving abilities.

3. Video or Phone Interviews

Candidates who pass the technical assessment will typically participate in one or more video or phone interviews. These interviews often involve discussions with team members, managers, or technical leads. Interviewers will ask about previous projects, technical skills, and how the candidate approaches data analysis and reporting. Expect questions that explore your experience with data integrity, database management, and analytical tools.

4. Onsite Interview or Final Round

The final stage of the interview process may include an onsite interview or a more in-depth virtual interview. This round often consists of multiple one-on-one interviews with various stakeholders, including managers and team members. Candidates may be asked to present a project or case study that demonstrates their analytical skills and ability to communicate complex data insights effectively. Behavioral questions will also be included to assess cultural fit and teamwork capabilities.

5. Wrap-Up and Offer

After the interviews, candidates will receive feedback from the interviewers. If selected, the candidate will be extended an offer, which may include discussions about salary, benefits, and other employment terms. The entire process can take several weeks, so patience is key.

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 Interview Structure

The interview process at Corning can be lengthy and may involve multiple rounds, including phone screenings, technical assessments, and in-person interviews. Be prepared for a variety of interview formats, including casual discussions with managers and technical quizzes. Familiarize yourself with the typical structure to manage your time and energy effectively.

Showcase Your Technical Skills

As a Data Analyst, you will be expected to demonstrate proficiency in SQL, data visualization tools like PowerBI, and a solid understanding of statistics and analytics. Brush up on your technical skills, particularly in SQL Server and TSQL, as interviewers often focus on these areas. Be ready to discuss your experience with data collection, analysis, and reporting, and provide specific examples of how you've used these skills in past projects.

Prepare for Behavioral Questions

Corning values candidates who can work collaboratively in a team environment. Expect behavioral questions that assess your problem-solving abilities, teamwork, and adaptability. Use the STAR (Situation, Task, Action, Result) method to structure your responses, highlighting your contributions to team projects and how you overcame challenges.

Be Ready to Present Your Work

Interviews may include a presentation of your past projects or experiences. Prepare a concise and engaging presentation that outlines your role, the technologies you used, and the impact of your work. Focus on how your contributions align with Corning's goals and values, emphasizing your ability to deliver quality work that exceeds expectations.

Emphasize Your Attention to Detail

Attention to detail is crucial in data analysis. Be prepared to discuss how you ensure data integrity and accuracy in your work. Share examples of how you've identified and resolved data discrepancies or improved data collection processes. This will demonstrate your commitment to delivering high-quality results.

Research the Company Culture

Corning places a strong emphasis on collaboration, innovation, and continuous improvement. Familiarize yourself with the company's values and recent initiatives. This knowledge will help you tailor your responses to align with the company's culture and demonstrate your genuine interest in being part of their team.

Ask Insightful Questions

Prepare thoughtful questions to ask your interviewers about the team dynamics, ongoing projects, and the company's future direction. This not only shows your interest in the role but also helps you assess if Corning is the right fit for you. Questions about how the data analyst role contributes to larger business objectives can be particularly impactful.

Follow Up Professionally

After the interview, send a thank-you email to express your appreciation for the opportunity to interview. Reiterate your interest in the position and briefly mention a key point from your discussion that reinforces your fit for the role. This small gesture can leave a positive impression and keep you top of mind as they make their decision.

By following these tips, you can present yourself as a well-prepared and enthusiastic candidate, ready to contribute to Corning's mission of innovation and excellence. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Analyst interview at Corning Incorporated. The interview process will likely focus on your technical skills, problem-solving abilities, and experience with data analysis tools and methodologies. Be prepared to discuss your past projects, your approach to data integrity, and how you can contribute to the team.

Technical Skills

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

Understanding SQL is crucial for a Data Analyst role, as it is often used for data manipulation and retrieval.

How to Answer

Discuss specific projects where you utilized SQL, mentioning the types of queries you wrote and the outcomes of your analyses.

Example

“In my previous role, I used SQL extensively to extract and analyze data from our customer database. I wrote complex queries to identify trends in customer behavior, which helped the marketing team tailor their campaigns effectively, resulting in a 15% increase in engagement.”

2. Describe a challenging data analysis project you worked on. What made it difficult and how did you overcome those challenges?

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

How to Answer

Focus on the specific challenges you faced, the steps you took to address them, and the final results of your project.

Example

“One of the most challenging projects involved cleaning a large dataset with numerous inconsistencies. I developed a systematic approach to identify and rectify errors, which included creating validation rules and using automated scripts. This not only improved data quality but also reduced processing time by 30%.”

3. How do you ensure data integrity in your analyses?

Data integrity is vital for accurate reporting and decision-making.

How to Answer

Explain the methods you use to validate data, such as cross-referencing with other sources or implementing checks during data entry.

Example

“I ensure data integrity by implementing validation checks at the point of data entry and regularly auditing datasets for discrepancies. Additionally, I use automated scripts to flag any anomalies, which allows for quick resolution before analysis.”

4. What data visualization tools are you familiar with, and how have you used them in your work?

Data visualization is key for presenting findings effectively.

How to Answer

Mention specific tools you have used, the types of visualizations you created, and how they helped communicate your findings.

Example

“I am proficient in Power BI and Tableau. In my last project, I created interactive dashboards that visualized sales trends over time, which provided the sales team with actionable insights and improved their forecasting accuracy.”

5. Can you describe your experience with data warehousing and ETL processes?

Understanding data warehousing and ETL (Extract, Transform, Load) processes is essential for managing large datasets.

How to Answer

Discuss your familiarity with data warehousing concepts and any specific ETL tools you have used.

Example

“I have experience with SQL Server Integration Services (SSIS) for ETL processes. I designed workflows to extract data from various sources, transform it for analysis, and load it into our data warehouse, ensuring that the data was always up-to-date and reliable for reporting.”

Behavioral Questions

1. Tell us about a time you had to work with a difficult stakeholder. How did you handle the situation?

This question evaluates your interpersonal skills and ability to manage relationships.

How to Answer

Describe the situation, your approach to communication, and the resolution.

Example

“I once worked with a stakeholder who was skeptical about the data-driven approach. I scheduled a meeting to understand their concerns and presented data in a way that aligned with their goals. By involving them in the analysis process, I was able to build trust and ultimately gain their support for the project.”

2. How do you prioritize your tasks when working on multiple projects?

Time management is crucial in a fast-paced environment.

How to Answer

Explain your method for prioritizing tasks, such as using project management tools or setting deadlines.

Example

“I prioritize tasks based on their impact and deadlines. I use tools like Trello to keep track of my projects and regularly reassess priorities based on any changes in project scope or urgency. This approach helps me stay organized and meet deadlines consistently.”

3. Describe a situation where you had to learn a new tool or technology quickly. How did you approach it?

This question assesses your adaptability and willingness to learn.

How to Answer

Share your learning strategy and how you applied the new knowledge.

Example

“When I needed to learn Power BI for a project, I dedicated time to online courses and hands-on practice. I also reached out to colleagues who were experienced with the tool for tips. Within a few weeks, I was able to create comprehensive dashboards that impressed our management team.”

4. How do you handle feedback on your analyses or reports?

Receiving and acting on feedback is essential for growth.

How to Answer

Discuss your openness to feedback and how you incorporate it into your work.

Example

“I view feedback as an opportunity for improvement. After presenting my analyses, I actively seek input from my peers and supervisors. I take their suggestions seriously and make adjustments to my reports to enhance clarity and effectiveness.”

5. What motivates you to excel in your role as a Data Analyst?

Understanding your motivation can help the interviewers gauge your fit within the company culture.

How to Answer

Share what drives you in your work, whether it’s problem-solving, making an impact, or continuous learning.

Example

“I am motivated by the challenge of turning complex data into actionable insights. Knowing that my analyses can influence strategic decisions and drive business success is incredibly fulfilling for me.”