Sr. Systems Engineer

The Sr. Systems Engineer at RELX Inc. is tasked with overseeing the development of software systems focused on cyber defense and personal data protection. This includes leading the creation of Machine Learning and data analytics software for fraud detection, guiding the adoption of BOT software for process automation, and participating in cloud migration efforts to Azure. Additionally, the role involves producing documentation for various software systems and assisting in cross-departmental projects.

Candidates applying for the Sr. Systems Engineer position at RELX Inc. should hold a Master’s degree in Computer Science, Computer Engineering, Information Systems, or a related field. Additionally, at least 2 years of experience in roles related to application development, particularly in cloud environments like Azure, AWS, or Google Cloud, is required. Familiarity with technologies such as Docker, CI/CD pipelines, and big data processing will also be essential.

Yes, the Sr. Systems Engineer role at RELX Inc. allows for telecommuting from any location within the U.S. while employees are expected to report to the office in Miamisburg, OH. This provides a flexible working arrangement for candidates interested in our innovative projects related to cyber security.

The Sr. Systems Engineer at RELX Inc. will work with a variety of advanced technologies, including Azure for cloud applications, Apache Spark for big data processing, and Python for data analytics applications. Familiarity with machine learning, data mining, and containerization technologies such as Docker will also be highly relevant to the role.

At RELX Inc., Sr. Systems Engineers can expect numerous career growth opportunities, including participation in innovative projects that drive the company's technology forward, opportunities for cross-department collaboration, and access to further training and professional development in cutting-edge technologies like machine learning and cloud computing.

When answering this question, focus on specific projects where you utilized Azure, AWS, or Google Cloud. Highlight your responsibilities, the technologies used, and the outcomes. Be sure to mention how you developed and deployed applications, managed data, or created CI/CD pipelines in these environments.

Outline your process for developing machine learning models, including data collection, preprocessing, model selection, training, and evaluation. Provide examples of how you have applied these models in real-world scenarios, especially in fraud detection or data analytics, which are relevant to the position.

Discuss your communication skills and tools that facilitate collaboration, such as project management software. Provide examples of projects where you worked with cross-functional teams, emphasizing how you ensured clear expectations and achieved shared goals.

Talk about your experience implementing process automation, such as through the use of BOT software or CI/CD pipelines. Highlight the specific tools you have used, the impact on productivity, and any metrics that showcase success in automating workflows.

Elaborate on your understanding of ETL (Extract, Transform, Load) processes, especially in big data contexts. Discuss how you've implemented ETL solutions, the tools you've used, and how this has benefited your projects, particularly in ensuring high data quality for analysis.

Detail your experience with big data technologies such as Apache Spark or Hadoop, including specific projects where you utilized these tools. Mention how you handled large datasets, processed them, and delivered meaningful insights or applications based on that data.

Identify a challenging situation you've faced when developing cloud applications, such as scaling issues, security concerns, or integration challenges. Discuss the solutions you implemented and the lessons learned, showing your problem-solving skills in real-world scenarios.

Share your approach to continuous learning, whether through online courses, attending conferences, or engaging in a professional network. Provide examples of how you’ve applied new knowledge or technologies in your work, particularly in relation to cyber security or cloud engineering.

Provide a detailed account of a specific project where you encountered significant software challenges. Discuss the troubleshooting process you followed, the tools or methodologies employed, and the final outcome. Highlight your analytical and technical skills.

Discuss the importance of APIs in your previous projects, focusing on how you've developed and used them to facilitate communication between different software components. Provide examples of integration efforts involving APIs and how they enhanced your application's functionality.