A Data Engineer at LexisNexis Risk Solutions plays a critical role in powering the data-driven products that industries rely on for fraud prevention, identity verification, and risk assessment. The company manages petabytes of complex, multi-sourced data, making the engineering pipelines that ingest, clean, and structure this information the backbone of the entire business. Without robust data engineering, the advanced analytics and risk models used by financial institutions, insurance providers, and government agencies would not function.

In this role, you will work within a highly specialized data ecosystem. Unlike standard open-source big data environments, LexisNexis Risk Solutions utilizes its own proprietary big data platform, HPCC Systems (High-Performance Computing Cluster), which runs on a declarative programming language called ECL (Enterprise Control Language). As a Data Engineer, your day-to-day work will involve taking data ingestion scripts provided by upstream teams, adapting them into standardized templates, and executing them at scale to ensure seamless data flow.

Joining the team means taking on significant operational responsibility. Your work directly impacts product reliability and data freshness, which is why scalability, optimization, and system stability are always top of mind. If you enjoy solving massive data challenges, mastering proprietary enterprise technologies, and taking ownership of end-to-end data delivery, this role offers an exceptionally impactful and technically rewarding career path.

The following questions are representative of what you can expect during the interview process for a Data Engineer position at LexisNexis Risk Solutions. These questions are compiled from real interview experiences to help you identify key patterns and themes, rather than to serve as a list for rote memorization.

Technical & Scripting Foundations

This category evaluates your fundamental command of data manipulation, query optimization, and scripting. Interviewers want to ensure you have the practical skills to handle complex data structures.

• Explain how you would optimize a slow-running SQL query that involves multiple large table joins.
• How do you manage file permissions and process execution in a Linux environment?

Preparing for an interview at LexisNexis Risk Solutions requires a balanced approach. You must demonstrate strong foundational technical skills while showing a high degree of adaptability and enthusiasm for learning proprietary technologies.

Role-Related Knowledge – You must show a deep, practical mastery of SQL and Linux, as these are the tools you will use daily to navigate databases and manage file systems. Additionally, having a solid foundation in an object-oriented language like C# is highly valued by many teams to help customize and troubleshoot integration scripts.

Learning Agility – Because the company utilizes HPCC Systems and ECL, you are not expected to know these proprietary systems on day one. Instead, interviewers will evaluate your ability to grasp complex, declarative programming concepts quickly. Focus on demonstrating how you have successfully mastered other niche or proprietary technologies in your past roles.

Problem-Solving Ability – You will be asked to walk through technical challenges you have faced in the past. Interviewers look for structured thinking, a methodical approach to debugging, and the ability to explain complex technical issues in a clear, concise manner.

Operational Ownership – The Data Engineer role comes with real-world operational responsibilities, including a shared on-call rotation. You must demonstrate that you are reliable, calm under pressure, and capable of taking ownership of production pipelines when issues arise.

The interview process for a Data Engineer at LexisNexis Risk Solutions is structured to evaluate both your technical capabilities and your behavioral alignment with the team. The process typically moves at a steady pace, starting with initial recruitment screens and progressing to deeper technical and managerial evaluations.

The journey begins with a standard recruiter phone screen to discuss your professional background, salary expectations, and overall alignment with the role. If there is a mutual fit, you will move into the technical screening phase, which often consists of one or two rounds focusing on your core engineering skills, particularly in SQL, Linux, and programming logic. The final stage is an interview with the hiring manager and key team members, where the focus shifts toward system design, operational responsibilities, and behavioral fit.

The timeline above outlines the standard progression from your initial application to the final hiring decision. Candidates should use this sequence to pace their preparation, focusing first on core technical fundamentals before diving into behavioral stories and system architecture. While the exact number of rounds can vary slightly depending on the seniority of the role and the specific team, this flow represents the typical candidate experience.

To succeed in the LexisNexis Risk Solutions interview process, you must understand the specific areas where candidates are evaluated most rigorously.

Data Manipulation & Platform Fundamentals

This area evaluates your hands-on capability to interact with operating systems and databases to move, transform, and query large datasets.

Be ready to go over:

• Advanced SQL – Complex joins, window functions, indexing strategies, and query execution plans.
• Linux Administration – Command-line utilities, shell scripting, file system navigation, and process monitoring.
• Object-Oriented Programming – Core concepts in C# or Java, particularly how they relate to data processing and system integration.

Example questions or scenarios:

• "Write a SQL query to find duplicate records in a massive transaction table and outline how you would delete them efficiently."
• "How would you write a bash script to monitor a directory for incoming files and trigger a processing job once they arrive?"

Proprietary Technology Adaptability

While you will be trained on the job, showing that you have the cognitive framework to learn HPCC Systems and ECL is a major competitive advantage.

Be ready to go over:

• Declarative Programming Concepts – Understanding how declarative languages differ from imperative ones.
• Data Workflows – How data is distributed, indexed, and queried across a clustered environment.
• Learning Methodology – Your personal strategy for rapidly onboarding onto proprietary or highly specialized enterprise tools.

Example questions or scenarios:

• "Explain a time when you had to adopt a brand-new, non-standard tool or language to complete a project. What challenges did you face, and how did you overcome them?"
• "How do you approach debugging a system when standard open-source documentation or community forums are not available?"

Operational & Behavioral Alignment

This area assesses your readiness to handle the day-to-day realities of the role, including teamwork, script templates, and production support.

Be ready to go over:

• On-Call Management – How you handle system alerts, prioritize incidents, and communicate during outages.
• Collaboration – Working with upstream teams who write the initial scripts that you will format, template, and run.
• Resilience – Overcoming setbacks, handling tight deadlines, and dealing with constructive feedback.

Example questions or scenarios:

• "Describe a time when a production pipeline failed during your shift. What immediate steps did you take to mitigate the impact?"
• "How do you ensure clear communication when transitioning on-call duties to another engineer?"

As a Data Engineer at LexisNexis Risk Solutions, your daily responsibilities center around the ingestion, processing, and management of critical data assets. You will not typically build data ingestion scripts entirely from scratch; instead, you will collaborate closely with other teams who provide the initial operational scripts. Your job is to take these scripts, refine them, integrate them into standardized templates, and execute them safely within the HPCC Systems cluster.