FIS Global Data Engineer Interview Questions + Guide in 2025

FIS Global is a leading fintech company that powers the world's economy through innovative technology solutions designed for the financial services industry.

As a Data Engineer at FIS, you will play a pivotal role in building and maintaining data pipelines that support the financial technology platforms utilized by various stakeholders within the organization. Your primary responsibilities will include designing efficient ETL processes to extract, transform, and load data from multiple sources, ensuring data integrity and availability for analysis and reporting. A strong emphasis will be placed on collaborating with cross-functional teams, including finance, operations, and engineering, to understand their data needs and deliver actionable insights that drive business decisions.

The ideal candidate will possess a Bachelor's degree in Computer Science or a related field, accompanied by at least 3 years of relevant experience in data engineering, analytics, or a similar role within the finance or technology domains. Proficiency in SQL, algorithms, and programming languages such as Python is essential, as well as strong analytical skills to identify trends and opportunities for process improvement.

This guide will help you prepare for your interview by providing insight into the skills and experiences that FIS values in a Data Engineer, as well as the types of questions you may encounter during the interview process.

The interview process for a Data Engineer role at FIS is structured to assess both technical and behavioral competencies, ensuring candidates are well-suited for the dynamic fintech environment. The process typically consists of several key stages:

1. Initial Screening

The first step is an initial phone screening with a recruiter, lasting about 30 minutes. During this conversation, the recruiter will discuss the role, the company culture, and your background. Expect to answer questions about your experience, motivation for applying, and how your skills align with the needs of FIS.

2. Technical Interview

Following the initial screening, candidates will participate in a technical interview, which may be conducted via video conferencing. This interview usually lasts around 1 to 1.5 hours and focuses on assessing your technical knowledge and problem-solving abilities. You can expect questions related to programming languages, data management, and specific technologies relevant to the role, such as SQL and ETL processes. Be prepared to demonstrate your understanding of data pipelines and your experience with data-related projects.

3. Behavioral Interview

After the technical interview, candidates typically undergo a behavioral interview. This round may involve one-on-one discussions with team members or managers. The focus here is on your past experiences, particularly how you have handled challenges in previous roles, collaborated with cross-functional teams, and contributed to data-driven decision-making. Expect questions that explore your communication skills and ability to work in a fast-paced environment.

4. Panel Interview

In some cases, candidates may face a panel interview, which includes multiple interviewers from different departments. This stage is designed to evaluate your fit within the team and the organization as a whole. You may be asked to present a case study or discuss specific projects you have worked on, highlighting your technical skills and collaborative efforts.

5. Final Interview

The final stage often involves a discussion with the hiring manager. This interview may include scenario-based questions that assess your technical expertise and your approach to problem-solving in real-world situations. You may also be asked about your long-term career goals and how you envision contributing to FIS.

As you prepare for your interview, keep in mind the specific skills and experiences that are highly valued for this role, particularly in data engineering and analytics.

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

Here are some tips to help you excel in your interview for the Data Engineer role at FIS.

Understand the Interview Structure

FIS typically conducts a multi-step interview process that includes an initial phone screening followed by technical interviews with team members and possibly a hiring manager. Familiarize yourself with this structure so you can prepare accordingly. Expect a mix of behavioral and technical questions, and be ready to discuss your past experiences in detail.

Prepare for Technical Proficiency

Given the emphasis on SQL and algorithms in this role, ensure you are well-versed in these areas. Brush up on complex SQL queries, including joins, subqueries, and performance tuning. Additionally, be prepared to solve algorithmic problems that demonstrate your problem-solving skills. Practice coding challenges that reflect real-world scenarios you might encounter in the role.

Showcase Your Project Experience

During the interview, be ready to discuss specific projects you've worked on, particularly those that involved data pipelines, ETL processes, or financial data analysis. Highlight your role in these projects, the technologies you used, and the impact your work had on the organization. This will demonstrate your hands-on experience and ability to contribute to FIS's goals.

Emphasize Collaboration and Communication Skills

FIS values cross-functional collaboration, so be prepared to discuss how you've worked with teams from different departments in the past. Share examples of how you effectively communicated technical concepts to non-technical stakeholders and how you contributed to team success. This will show that you can thrive in FIS's inclusive and diverse work environment.

Be Ready for Behavioral Questions

Expect behavioral questions that assess your soft skills, such as conflict resolution and adaptability. Use the STAR (Situation, Task, Action, Result) method to structure your responses. For instance, you might be asked about a time you dealt with a difficult coworker or how you managed a tight deadline. Prepare specific examples that highlight your problem-solving abilities and resilience.

Align with Company Culture

FIS promotes a culture of innovation and community involvement. Research the company's values and recent initiatives, and think about how your personal values align with theirs. Be prepared to discuss how you can contribute to FIS's mission of advancing fintech solutions and supporting community initiatives.

Follow Up with Questions

At the end of the interview, take the opportunity to ask insightful questions about the team, projects, and company culture. This not only shows your interest in the role but also helps you assess if FIS is the right fit for you. Consider asking about the technologies the team is currently using or how they measure success in their projects.

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

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at FIS. The interview process will likely focus on your technical expertise, problem-solving skills, and ability to work collaboratively across teams. Be prepared to discuss your experience with data management, SQL, ETL processes, and your understanding of financial data.

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 data quality and accessibility for analysis.

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 data warehouse. This process ensures that data is clean, consistent, and readily available for analysis, which is essential for making informed business decisions.”

2. What strategies do you use to optimize SQL queries?

Optimizing SQL queries is vital for improving performance and efficiency in data retrieval.

How to Answer

Mention specific techniques such as indexing, query restructuring, and analyzing execution plans to enhance performance.

Example

“I optimize SQL queries by using indexing to speed up data retrieval, restructuring complex queries to reduce execution time, and analyzing execution plans to identify bottlenecks. For instance, I once improved a report generation query by 50% by adding appropriate indexes and simplifying the joins.”

3. Describe your experience with data pipeline management.

Data pipeline management is a key responsibility for a Data Engineer, and your experience in this area will be closely scrutinized.

How to Answer

Share specific tools and technologies you have used, along with examples of how you managed data pipelines effectively.

Example

“I have extensive experience managing data pipelines using tools like Apache Airflow and AWS Glue. In my previous role, I designed a pipeline that automated the ETL process for financial data, which reduced manual intervention by 70% and improved data accuracy.”

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

Data quality and integrity are paramount in financial data engineering.

How to Answer

Discuss methods you employ to validate and clean data, as well as monitoring processes to maintain data integrity.

Example

“I ensure data quality by implementing validation checks at various stages of the ETL process, such as verifying data types and ranges. Additionally, I set up monitoring alerts to catch anomalies in real-time, which allows for immediate corrective actions.”

5. Can you explain a challenging data-related problem you faced and how you resolved it?

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

How to Answer

Provide a specific example that highlights your analytical skills and the steps you took to resolve the issue.

Example

“I once faced a challenge where data from multiple sources had inconsistent formats, which caused issues in reporting. I developed a transformation script that standardized the data formats before loading them into the warehouse. This not only resolved the immediate issue but also improved the overall data processing time by 30%.”

Behavioral Questions

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

Collaboration is essential in a role that requires working with various stakeholders.

How to Answer

Share an example that illustrates your teamwork and communication skills.

Example

“In my last project, I collaborated with finance and engineering teams to develop a new reporting tool. I facilitated regular meetings to gather requirements and ensure alignment, which resulted in a tool that met everyone’s needs and was delivered on time.”

2. How do you handle tight deadlines and pressure?

Working in a fast-paced environment often involves managing tight deadlines.

How to Answer

Discuss your time management strategies and how you prioritize tasks under pressure.

Example

“I handle tight deadlines by breaking down projects into manageable tasks and prioritizing them based on urgency and impact. For instance, during a recent project, I created a timeline with milestones, which helped me stay focused and deliver the final product ahead of schedule.”

3. Tell me about a time you had to deal with a difficult coworker.

This question assesses your interpersonal skills and conflict resolution abilities.

How to Answer

Provide a specific example that demonstrates your ability to navigate workplace challenges diplomatically.

Example

“I once worked with a colleague who had a different approach to data analysis, which led to conflicts. I initiated a one-on-one discussion to understand their perspective and shared my insights. This open communication helped us find common ground and ultimately improved our collaboration on the project.”

4. What motivates you to work in the fintech industry?

Understanding your motivation can help interviewers gauge your passion for the role.

How to Answer

Share your interest in fintech and how it aligns with your career goals.

Example

“I am motivated by the rapid innovation in the fintech industry and the opportunity to work on projects that have a real impact on people’s financial lives. I find it rewarding to contribute to solutions that enhance financial accessibility and efficiency.”

5. How do you stay updated with the latest trends in data engineering?

This question assesses your commitment to continuous learning and professional development.

How to Answer

Discuss the resources you use to stay informed about industry trends and technologies.

Example

“I stay updated by following industry blogs, participating in webinars, and attending conferences. I also engage with online communities and forums where data engineers share insights and best practices, which helps me stay current with emerging technologies and methodologies.”