NCR Corporation Data Engineer Interview Questions + Guide in 2025

NCR Corporation, a leader in digital commerce solutions, empowers businesses in retail, restaurant, and banking industries through innovative technology and exceptional consumer experiences.

As a Data Engineer at NCR, you will play a crucial role in developing and maintaining robust data pipelines that support the company's mission of enabling clients to exceed their operational goals. Your key responsibilities will include collaborating with business unit leaders to analyze and design data products, ensuring the integrity and cleanliness of data, and leveraging cloud-based technologies to build scalable solutions. Required skills for this role encompass proficiency in SQL, Python, and familiarity with big data frameworks such as Hadoop, as well as experience with data visualization tools like Tableau. A strong analytical mindset, attention to detail, and an ability to work collaboratively across teams are essential traits for success in this position.

This guide will help you prepare for your interview by highlighting the core competencies and knowledge areas you'll need to showcase, as well as providing insights into the company's values and expectations.

The interview process for a Data Engineer position at NCR Corporation is structured to assess both technical skills and cultural fit within the organization. It typically consists of several key stages:

1. HR Interview

The first step in the interview process is a conversation with an HR representative. This initial interview is designed to gauge your interest in the role and the company, as well as to discuss your background and experiences. The HR interview is generally described as pleasant and conversational, allowing candidates to express their motivations and career aspirations. Expect questions that explore your understanding of the company’s mission and how your values align with NCR's commitment to diversity and customer-centric solutions.

2. Technical Interview

Following the HR interview, candidates will participate in a technical interview. This round focuses on assessing your technical knowledge and problem-solving abilities relevant to data engineering. Questions may cover fundamental concepts in data management, SQL, Python, and data pipeline construction. Candidates should be prepared to discuss their experience with data architecture, data cleanliness, and the tools they have used in previous projects. The technical interview is typically described as approachable, with an emphasis on foundational knowledge rather than overly complex problems.

3. Final Steps

After the technical interview, candidates may experience a waiting period before receiving an offer. This period can vary, but it is not uncommon for candidates to wait a few weeks. If selected, candidates can expect to receive an offer letter promptly, often within a day or two of the final interview.

As you prepare for your interview, it’s essential to familiarize yourself with the types of questions that may arise during the process.

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

Understand the Company’s Mission and Values

NCR Corporation places a strong emphasis on customer satisfaction and operational excellence. Familiarize yourself with their mission to empower businesses in the retail, restaurant, and banking sectors. Be prepared to discuss how your skills as a Data Engineer can contribute to enhancing customer experiences and driving revenue growth. Show that you align with their commitment to diversity and inclusion, as this is a core value of the company.

Master the Basics of Data Engineering

While the interviews may not delve into overly complex topics, a solid grasp of fundamental concepts is crucial. Be prepared to discuss Hadoop architecture, its components, and how they relate to data processing. Brush up on SQL, focusing on joins, subqueries, and data manipulation techniques. Additionally, ensure you can articulate your experience with Python and any relevant data visualization tools like Tableau, as these are likely to come up during technical discussions.

Prepare for a Two-Part Interview Structure

Expect a pleasant HR interview followed by a technical interview. The HR round will likely assess your cultural fit and soft skills, so be ready to share examples of teamwork, problem-solving, and adaptability. In the technical round, focus on articulating your thought process clearly. When answering questions, take a moment to think through your responses, and don’t hesitate to ask for clarification if needed. This shows your analytical approach and willingness to engage in a dialogue.

Showcase Your Problem-Solving Skills

During the technical interview, you may be presented with scenarios or problems to solve. Approach these questions methodically: clarify the problem, outline your thought process, and discuss potential solutions. Highlight your experience in building scalable data pipelines and ensuring data cleanliness, as these are key responsibilities of the role. Use specific examples from your past work to illustrate your capabilities.

Emphasize Collaboration and Communication

Given that the role involves partnering with various teams, emphasize your ability to work collaboratively. Discuss experiences where you successfully communicated complex data concepts to non-technical stakeholders or collaborated with cross-functional teams. This will demonstrate your interpersonal skills and your understanding of the importance of teamwork in delivering quality data products.

Follow Up with Insightful Questions

At the end of the interview, take the opportunity to ask insightful questions about the team dynamics, ongoing projects, or the technologies they are currently using. This not only shows your genuine interest in the role but also allows you to assess if the company culture and work environment align with your career goals.

By preparing thoroughly and demonstrating your alignment with NCR Corporation's values and mission, you will 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 NCR Corporation. The interview process will likely assess your technical skills in data management, cloud technologies, and your ability to work with various data tools and frameworks. Be prepared to demonstrate your understanding of data pipelines, SQL, and data architecture concepts.

Technical Skills

1. Can you explain the architecture of Hadoop and its key components?

Understanding Hadoop is crucial for a Data Engineer role, as it is often used for big data processing.

How to Answer

Discuss the core components of Hadoop, including HDFS, MapReduce, and YARN, and how they interact to process large datasets.

Example

“Hadoop architecture consists of HDFS for storage, which allows for distributed data storage across multiple nodes, and MapReduce for processing that data in parallel. YARN acts as the resource manager, ensuring efficient resource allocation for various applications running on the cluster.”

2. What are the different types of joins in SQL, and when would you use each?

SQL proficiency is essential for data manipulation and retrieval.

How to Answer

Explain the various types of joins (INNER, LEFT, RIGHT, FULL OUTER) and provide scenarios for their use.

Example

“INNER JOIN is used when you want to retrieve records that have matching values in both tables, while LEFT JOIN retrieves all records from the left table and matched records from the right. For instance, I would use a LEFT JOIN to get all customers and their orders, even if some customers have not placed any orders.”

3. Describe a subquery and provide an example of when you would use one.

Subqueries are a common SQL feature that can simplify complex queries.

How to Answer

Define a subquery and explain its purpose, along with a practical example.

Example

“A subquery is a query nested within another SQL query. I would use a subquery to filter results based on aggregated data, such as finding all employees whose salaries are above the average salary of their department.”

4. How do you ensure data quality and cleanliness in your data pipelines?

Data integrity is vital for accurate analysis and reporting.

How to Answer

Discuss the methods you use to validate and clean data, such as data profiling, validation rules, and automated checks.

Example

“I implement data validation rules at the point of entry and regularly perform data profiling to identify anomalies. Additionally, I use automated scripts to clean and standardize data before it enters the pipeline, ensuring that only high-quality data is processed.”

5. What experience do you have with cloud-based data solutions, particularly Azure?

Familiarity with cloud platforms is increasingly important for data engineering roles.

How to Answer

Share your experience with Azure services, such as Azure Data Lake, Azure SQL Database, or Azure Data Factory, and how you have utilized them in past projects.

Example

“I have worked extensively with Azure Data Lake for storing large datasets and Azure Data Factory for orchestrating data workflows. In my last project, I used Azure Data Factory to automate the ETL process, which significantly reduced the time taken to prepare data for analysis.”

Data Tools and Technologies

1. What is your experience with Python for data engineering tasks?

Python is a popular language for data manipulation and analysis.

How to Answer

Discuss your proficiency in Python and how you have used it in data engineering tasks, such as data transformation or automation.

Example

“I have used Python extensively for data manipulation using libraries like Pandas and NumPy. For instance, I developed a script that automated the data cleaning process, which saved my team several hours each week.”

2. How do you approach designing a scalable data pipeline?

Scalability is a key consideration in data engineering.

How to Answer

Explain the principles you follow when designing data pipelines, including modularity, performance optimization, and monitoring.

Example

“When designing a scalable data pipeline, I focus on modular architecture, allowing for easy updates and maintenance. I also implement performance monitoring tools to identify bottlenecks and optimize data flow, ensuring the pipeline can handle increased loads as data volume grows.”

3. Can you describe your experience with data visualization tools like Tableau?

Data visualization is important for presenting insights effectively.

How to Answer

Share your experience with Tableau or similar tools and how you have used them to communicate data insights.

Example

“I have used Tableau to create interactive dashboards that visualize key performance metrics for stakeholders. By connecting Tableau to our data warehouse, I was able to provide real-time insights that helped drive strategic decisions.”

4. What strategies do you use for optimizing SQL queries?

Query optimization is essential for performance in data retrieval.

How to Answer

Discuss techniques you use to improve SQL query performance, such as indexing, query restructuring, or analyzing execution plans.

Example

“I optimize SQL queries by using indexing on frequently queried columns and restructuring complex queries to reduce the number of joins. Additionally, I analyze execution plans to identify slow-running queries and make necessary adjustments.”

5. How do you handle version control for your data engineering projects?

Version control is important for collaboration and project management.

How to Answer

Explain your approach to using version control systems like Git for managing code and collaboration.

Example

“I use Git for version control in my data engineering projects, allowing me to track changes and collaborate effectively with my team. I follow best practices by creating branches for new features and regularly merging changes to maintain a clean and organized codebase.”