Fiserv Data Engineer Interview Questions + Guide in 2025

Fiserv is a global leader in Fintech and payments, facilitating secure and efficient transactions for millions of customers worldwide.

The Data Engineer at Fiserv plays a critical role in the design, implementation, and maintenance of data architectures and pipelines that ensure the seamless flow of data across the organization. This position requires a strong proficiency in SQL, particularly in crafting complex queries and managing data relationships to avoid duplicates, as well as a deep understanding of big data technologies and cloud-native solutions, particularly within the Azure ecosystem, including Azure Databricks, Azure Data Lake Storage, and Azure Synapse. A successful candidate will be adept at troubleshooting and optimizing data pipelines, ensuring data quality and integrity, and collaborating effectively with cross-functional teams to translate business requirements into technical solutions.

In alignment with Fiserv's commitment to innovation and excellence, the ideal Data Engineer will demonstrate strong problem-solving skills, attention to detail, and the ability to thrive in a fast-paced environment. This guide will help you prepare for your interview by providing insights into the technical skills and traits that Fiserv values in their Data Engineers, enabling you to present yourself as a well-rounded candidate ready to contribute to their mission.

The interview process for a Data Engineer position at Fiserv is structured to assess both technical skills and cultural fit within the organization. It typically consists of several key stages, each designed to evaluate different aspects of your qualifications and experience.

1. Initial Screening

The first step in the interview process is an initial screening, which usually takes place over the phone. During this 30-minute conversation, a recruiter will discuss your background, experience with data engineering, and familiarity with SQL and Azure technologies. This is also an opportunity for you to learn more about Fiserv's culture and the specifics of the Data Engineer role.

2. Technical Assessment

Following the initial screening, candidates will undergo a technical assessment, which may be conducted via a video call. This assessment focuses heavily on your SQL skills, particularly your ability to write complex queries and handle data manipulation tasks. You may be presented with scenarios involving big data and asked to demonstrate your problem-solving skills in real-time. Expect to answer questions related to data pipeline management and your experience with Azure Databricks or similar platforms.

3. Onsite Interview

The final stage of the interview process is an onsite interview, which is more comprehensive and interactive. This typically includes a workshop where you will be required to write SQL queries and present your solutions to a panel of interviewers. The focus will be on your ability to work with many-to-many relationships and avoid common pitfalls such as creating duplicates in your data. Additionally, you may be asked to discuss your previous projects, detailing your role in data integration and transformation processes.

Throughout the onsite interview, expect to engage in discussions about your experience with Azure technologies, data modeling, and your approach to troubleshooting and optimizing data pipelines. This stage is crucial for demonstrating your technical expertise and your ability to collaborate with cross-functional teams.

As you prepare for your interview, consider the specific skills and experiences that align with the requirements of the Data Engineer role at Fiserv. The next section will delve into the types of questions you may encounter during the interview process.

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

Master SQL and Data Handling

Given the emphasis on SQL in the interview process, ensure you are well-versed in writing complex queries, particularly those involving joins and handling many-to-many relationships. Practice SQL problems that require you to manipulate data effectively, as this will likely be a focal point during your technical assessments. Be prepared to discuss your experience with SQL in detail, including specific challenges you've faced and how you overcame them.

Understand Big Data Concepts

Since the role involves handling big data, familiarize yourself with the principles of big data architecture and processing. Be ready to discuss your experience with data pipelines, data lakes, and cloud technologies, particularly Azure Databricks. Highlight any projects where you successfully managed large datasets or implemented data solutions that improved efficiency or performance.

Showcase Your Experience with Azure Technologies

As a Data Engineer at Fiserv, you will be expected to work extensively with Azure technologies. Be prepared to discuss your experience with Azure Data Lake Storage, Azure Databricks, and any other relevant Azure services. If you have experience with Infrastructure as Code (IaC) tools like Terraform, make sure to mention it, as this could set you apart from other candidates.

Communicate Effectively

Effective communication is crucial, especially when collaborating with cross-functional teams. Be prepared to demonstrate your ability to adapt your communication style to different audiences, whether technical or non-technical. Share examples of how you've successfully communicated complex data concepts to stakeholders in the past.

Prepare for Practical Assessments

Expect practical assessments during the interview process, including SQL tests and possibly a workshop where you will need to present your work. Practice explaining your thought process as you solve problems, as this will showcase your analytical skills and ability to work under pressure.

Emphasize Security Awareness

Given the importance of security in data management, be ready to discuss how you ensure data security and integrity in your projects. Share any experiences you have with identifying and mitigating security vulnerabilities in database technologies.

Align with Company Culture

Fiserv values innovation and excellence, so be sure to convey your passion for technology and your commitment to continuous improvement. Research the company’s recent initiatives and be prepared to discuss how your skills and experiences align with their goals. Demonstrating a genuine interest in Fiserv's mission and values will help you stand out as a candidate.

By focusing on these areas, you will be well-prepared to make a strong impression during your interview for the Data Engineer role at Fiserv. Good luck!

In this section, we’ll review the various interview questions that might be asked during a Data Engineer interview at Fiserv. The interview process will focus heavily on your technical skills, particularly in SQL, Azure technologies, and data pipeline management. Be prepared to demonstrate your understanding of data integration, transformation processes, and your ability to troubleshoot and optimize data workflows.

SQL and Database Management

1. Can you explain the difference between INNER JOIN and LEFT JOIN in SQL?

Understanding SQL joins is crucial for data manipulation and retrieval.

How to Answer

Discuss the definitions of both INNER JOIN and LEFT JOIN, emphasizing how they differ in terms of the records they return from the tables involved.

Example

"An INNER JOIN returns only the rows where there is a match in both tables, while a LEFT JOIN returns all rows from the left table and the matched rows from the right table. If there is no match, NULL values are returned for columns from the right table."

2. How do you handle duplicate records in SQL?

This question assesses your data cleaning skills.

How to Answer

Explain the methods you use to identify and remove duplicates, such as using the DISTINCT keyword or the ROW_NUMBER() function.

Example

"I typically use the ROW_NUMBER() function to assign a unique identifier to each row within a partition of duplicates, then I can filter out the duplicates based on that identifier. This ensures that I retain only the necessary records."

3. Describe a complex SQL query you have written. What was its purpose?

This question evaluates your practical experience with SQL.

How to Answer

Provide a brief overview of the query, its components, and the problem it solved.

Example

"I wrote a complex SQL query to aggregate sales data from multiple tables, joining them on various keys to generate a comprehensive report for the sales team. The query utilized multiple joins and subqueries to ensure accurate data representation."

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

This question tests your knowledge of performance tuning.

How to Answer

Discuss techniques such as indexing, query restructuring, and analyzing execution plans.

Example

"I optimize SQL queries by creating appropriate indexes on frequently queried columns, rewriting queries to reduce complexity, and analyzing execution plans to identify bottlenecks."

5. How do you ensure data integrity in your SQL databases?

This question assesses your understanding of data quality.

How to Answer

Explain the measures you take to maintain data integrity, such as constraints and validation checks.

Example

"I ensure data integrity by implementing primary and foreign key constraints, using transactions to maintain consistency, and performing regular data validation checks."

Data Pipeline and ETL Processes

1. Can you describe your experience with Azure Data Lake Storage?

This question focuses on your familiarity with Azure technologies.

How to Answer

Discuss your experience with Azure Data Lake Storage, including its features and how you've used it in projects.

Example

"I have extensive experience with Azure Data Lake Storage, where I utilized it to store large volumes of structured and unstructured data. I implemented data ingestion pipelines that efficiently moved data into the lake for further processing."

2. How do you design a data pipeline for ETL processes?

This question evaluates your understanding of ETL architecture.

How to Answer

Outline the steps you take in designing an ETL pipeline, including data extraction, transformation, and loading.

Example

"I start by identifying the data sources and defining the extraction methods. Then, I design the transformation logic to clean and format the data before loading it into the target system, ensuring that the pipeline is scalable and efficient."

3. What tools have you used for data integration and transformation?

This question assesses your toolset and experience.

How to Answer

Mention specific tools you have used, such as Azure Data Factory, and describe their functionalities.

Example

"I have used Azure Data Factory for orchestrating data workflows and transforming data using mapping data flows. It allows me to create complex ETL processes with minimal coding."

4. Describe a challenge you faced while building a data pipeline and how you overcame it.

This question tests your problem-solving skills.

How to Answer

Share a specific example of a challenge, the steps you took to resolve it, and the outcome.

Example

"I faced a challenge with data latency in a real-time pipeline. To overcome this, I implemented a more efficient data batching strategy and optimized the transformation logic, which significantly reduced the processing time."

5. How do you monitor and troubleshoot data pipelines?

This question evaluates your operational skills.

How to Answer

Discuss the tools and techniques you use for monitoring and troubleshooting.

Example

"I use Azure Monitor and Log Analytics to track the performance of my data pipelines. When issues arise, I analyze the logs to identify bottlenecks and implement fixes to ensure smooth operation."

Cloud Technologies

1. What is your experience with Azure Databricks?

This question focuses on your experience with cloud-based data solutions.

How to Answer

Describe your experience with Azure Databricks, including specific projects or tasks.

Example

"I have used Azure Databricks to build scalable data processing solutions, leveraging its capabilities for big data analytics and machine learning. I particularly enjoyed using its collaborative notebooks for team projects."

2. How do you ensure security in your data solutions?

This question assesses your understanding of data security practices.

How to Answer

Discuss the security measures you implement in your data solutions.

Example

"I ensure security by implementing role-based access control, encrypting sensitive data both at rest and in transit, and regularly auditing access logs to detect any unauthorized access."

3. Can you explain the concept of Infrastructure as Code (IaC) and its benefits?

This question evaluates your knowledge of modern deployment practices.

How to Answer

Define IaC and discuss its advantages in managing cloud infrastructure.

Example

"Infrastructure as Code allows us to manage and provision cloud resources using code, which enhances consistency and reduces manual errors. It also enables version control and easier collaboration among team members."

4. Describe your experience with Azure Event Hubs.

This question focuses on your experience with event streaming technologies.

How to Answer

Explain how you have used Azure Event Hubs in your projects.

Example

"I have utilized Azure Event Hubs for real-time data ingestion from various sources, allowing me to process and analyze streaming data efficiently. It was particularly useful in scenarios requiring low-latency data processing."

5. How do you approach cloud data migrations?

This question assesses your experience with cloud transitions.

How to Answer

Discuss your strategy for migrating data to the cloud, including planning and execution.

Example

"I approach cloud data migrations by first assessing the existing data architecture and identifying dependencies. I then create a detailed migration plan, ensuring minimal downtime and data integrity throughout the process."