Steris Corporation Data Engineer Interview Questions + Guide in 2025

Steris Corporation is a leading global provider of innovative healthcare and life science products and services that support patient care with an emphasis on infection prevention.

The Data Engineer plays a critical role at Steris Corporation by overseeing the design, development, deployment, and maintenance of scalable data solutions that meet the diverse needs of the organization. This position encompasses managing data integration pipelines to connect various data sources, collaborating with data architects and data scientists, and ensuring the optimization of data processing for quality and security. A successful Data Engineer at Steris will demonstrate advanced proficiency in SQL, experience with cloud technologies, and a solid understanding of data governance. They should possess strong project management skills, be adept at problem-solving, and have the ability to communicate effectively with both technical and non-technical stakeholders. This role aligns with Steris's commitment to creating a healthier and safer world by leveraging data to enhance healthcare outcomes.

This guide will help you prepare thoroughly for your Data Engineer interview at Steris Corporation, equipping you with the insights needed to showcase your skills and experiences effectively.

The interview process for a Data Engineer position at Steris Corporation is structured to assess both technical and interpersonal skills, ensuring candidates are well-suited for the collaborative and innovative environment of the company. The process typically consists of several key stages:

1. Initial Screening

The first step is an initial phone screening with a recruiter. This conversation lasts about 30-45 minutes and focuses on your background, experience, and motivation for applying to Steris. The recruiter will also provide insights into the company culture and the specifics of the Data Engineer role, allowing you to gauge if it aligns with your career goals.

2. Technical Interview

Following the initial screening, candidates usually participate in a technical interview, which may be conducted via video call. This interview typically lasts around an hour and includes a mix of technical and behavioral questions. You can expect to discuss your experience with data pipelines, SQL, and any relevant technologies. Be prepared to explain your thought process and problem-solving approach, as interviewers often seek to understand how you would handle real-world scenarios.

3. Behavioral Interview

The next round often involves a behavioral interview, which may be conducted by the HR team and the department lead. This interview is conversational in nature and focuses on your past experiences, teamwork, and how you handle various situations. Expect questions that explore your ability to collaborate with clients and development teams, as well as your approach to challenges in a data engineering context.

4. Onsite Interview

The final stage typically includes an onsite interview, which may consist of multiple one-on-one sessions with team members and managers. These interviews delve deeper into your technical skills, including your understanding of data architecture, ETL processes, and cloud technologies. You may also be asked to complete a technical assessment or case study that evaluates your ability to design and implement data solutions.

Throughout the interview process, candidates are encouraged to ask questions and engage with interviewers to demonstrate their interest in the role and the company.

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

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

Emphasize Your Technical Expertise

As a Data Engineer at Steris Corporation, you will be expected to demonstrate a strong command of data architecture, ETL processes, and SQL optimization. Be prepared to discuss your experience with various data integration tools and cloud technologies, as well as your familiarity with big data frameworks. Highlight specific projects where you successfully designed and implemented data solutions, and be ready to explain the technical decisions you made and their impact on the business.

Prepare for Behavioral Questions

Expect a significant focus on behavioral questions during your interviews. Steris values teamwork and collaboration, so be ready to share examples of how you've worked effectively in teams, resolved conflicts, or led projects. Use the STAR (Situation, Task, Action, Result) method to structure your responses, ensuring you convey not just what you did, but also the thought process behind your actions and the outcomes achieved.

Understand the Company Culture

Steris Corporation promotes a culture of innovation and continuous improvement. Familiarize yourself with their mission to create a healthier and safer world, and think about how your values align with this mission. During the interview, express your enthusiasm for contributing to this goal and share any relevant experiences that demonstrate your commitment to quality and safety in your work.

Be Ready for Technical Assessments

Technical assessments are a key part of the interview process for Data Engineers at Steris. You may be asked to explain complex technical concepts or walk through your thought process in designing data solutions. Practice articulating your technical knowledge clearly and concisely, and be prepared to tackle hypothetical scenarios that test your problem-solving skills.

Dress Appropriately and Be Mindful of First Impressions

While Steris promotes a relaxed environment, it’s important to dress professionally for your interview. Pay attention to the details, as first impressions matter. Choose attire that reflects your professionalism while still being comfortable. Additionally, be mindful of how you speak about your previous employers; focus on positive aspects and your desire for growth rather than any negatives.

Communicate Effectively

Strong communication skills are essential for a Data Engineer, especially when collaborating with cross-functional teams. Practice explaining technical concepts in a way that is accessible to non-technical stakeholders. During the interview, demonstrate your ability to listen actively and engage in meaningful dialogue with your interviewers.

Follow Up Thoughtfully

After your interview, consider sending a thank-you note to express your appreciation for the opportunity to interview. Use this as a chance to reiterate your interest in the role and briefly mention a key point from your discussion that reinforces your fit for the position. This not only shows your professionalism but also keeps you top of mind for the interviewers.

By following these tips, you can present yourself as a strong candidate who is not only technically proficient but also a great cultural fit for Steris Corporation. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Steris Corporation. The interview process will likely focus on your technical expertise, problem-solving abilities, and experience in data management and engineering. Be prepared to discuss your past projects, your approach to data architecture, and how you collaborate with cross-functional teams.

Technical Skills

1. Can you explain the differences between ETL and ELT processes?

Understanding the nuances between these two data processing methods is crucial for a Data Engineer role.

How to Answer

Discuss the definitions of ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform), highlighting when to use each based on data volume and processing needs.

Example

“ETL is typically used when data needs to be transformed before loading into the target system, which is ideal for smaller datasets. In contrast, ELT allows for loading raw data into the target system first, which is more efficient for larger datasets, especially in cloud environments where storage is less of a concern.”

2. Describe your experience with SQL optimization. What techniques do you use?

SQL optimization is a key skill for managing large datasets effectively.

How to Answer

Mention specific techniques such as indexing, query rewriting, and analyzing execution plans to improve performance.

Example

“I focus on indexing frequently queried columns and rewriting complex joins into simpler subqueries. Additionally, I regularly analyze execution plans to identify bottlenecks and adjust my queries accordingly to enhance performance.”

3. What is your experience with cloud data solutions, and which platforms have you used?

Cloud technologies are integral to modern data engineering.

How to Answer

Discuss your familiarity with various cloud platforms and specific services you have utilized for data storage and processing.

Example

“I have extensive experience with AWS, particularly using Redshift for data warehousing and S3 for storage. I’ve also worked with Azure Data Lake for big data processing, leveraging its scalability for large datasets.”

4. Can you explain what a star schema is and when you would use it?

Data modeling is a fundamental aspect of data architecture.

How to Answer

Define a star schema and explain its advantages in terms of query performance and simplicity.

Example

“A star schema is a type of database schema that organizes data into fact and dimension tables. It’s beneficial for analytical queries because it simplifies the structure, making it easier to understand and faster to query, especially in a data warehouse environment.”

5. How do you ensure data quality and integrity in your projects?

Data quality is critical for reliable analytics.

How to Answer

Discuss your strategies for data validation, cleansing, and monitoring throughout the data pipeline.

Example

“I implement data validation checks at various stages of the pipeline, such as schema validation and anomaly detection. Additionally, I regularly monitor data quality metrics and set up alerts for any discrepancies to ensure integrity.”

Behavioral Questions

1. Describe a technical project you led. What challenges did you face?

This question assesses your leadership and problem-solving skills.

How to Answer

Outline the project scope, your role, and specific challenges you encountered, along with how you overcame them.

Example

“I led a project to migrate our on-premise data warehouse to a cloud-based solution. One challenge was ensuring minimal downtime during the transition. I coordinated with stakeholders to develop a phased migration plan, which allowed us to maintain operations while gradually moving data.”

2. How do you handle conflicts within a team?

Collaboration is key in data engineering roles.

How to Answer

Provide an example of a conflict and how you facilitated a resolution.

Example

“In a previous project, there was a disagreement between team members on the data modeling approach. I organized a meeting where each person could present their perspective, and we collectively evaluated the pros and cons. This open dialogue led to a consensus on the best approach, strengthening our collaboration.”

3. Can you give an example of how you have improved a process in your previous role?

This question evaluates your initiative and continuous improvement mindset.

How to Answer

Discuss a specific process you improved, the steps you took, and the impact of that improvement.

Example

“I noticed that our data ingestion process was taking too long due to manual steps. I automated several tasks using Python scripts, which reduced the processing time by 40% and allowed the team to focus on more strategic initiatives.”

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

Time management is essential in a fast-paced environment.

How to Answer

Explain your approach to prioritization, including any tools or methods you use.

Example

“I use a combination of project management tools and the Eisenhower Matrix to prioritize tasks based on urgency and importance. This helps me focus on high-impact activities while ensuring that deadlines are met across all projects.”

5. Describe a time when you had to learn a new technology quickly. How did you approach it?

Adaptability is crucial in the tech field.

How to Answer

Share your learning strategy and how you applied the new technology in your work.

Example

“When I needed to learn Apache Spark for a project, I dedicated time to online courses and hands-on practice. I also joined community forums to ask questions and share knowledge, which accelerated my understanding and allowed me to implement Spark effectively in our data processing pipeline.”