Senior Data Engineer II

RELX (LexisNexis USA) is seeking a Senior Data Engineer II for a hybrid role in Irving, TX. The position focuses on daily data loads, complex data engineering troubleshooting, and the design and execution of advanced data models and ETL workflows, with additional work supporting ML-based application development and deployment across multiple environments.

Role Overview

The Senior Data Engineer II is responsible for performing daily data loads with recurring update logging and tracking, delivering efficient and repeatable code aligned with best practices, and contributing to system components of moderate complexity. The role also includes solving complex data engineering bugs by researching and identifying root causes, translating product requirements into data engineering and data management designs, and supporting ML-based application development and deployment workflows. Mentoring junior data engineers is included.

Key Responsibilities

• Perform daily data loads, ensuring recurring updates are logged and tracked.
• Coordinate with technical personnel to document, interpret, and finalize requirements.
• Write code that is efficient, repeatable, and free of defects while following best practices such as naming conventions and encapsulation.
• Contribute to detailed specifications for developing system components of moderate complexity.
• Complete complex data engineering bug fixes, resolving related issues and researching root causes as needed.
• Collaborate with development team members to understand complex product requirements and translate them into data engineering and/or data management designs.
• Drive process improvements to support efficient delivery and long-term maintenance.
• Apply development processes, coding best practices, and code review practices.
• Operate effectively across multiple development environments, including Agile and Waterfall, with key stakeholders.
• Identify opportunities to improve overall quality by working with other teams and peers, implementing initiatives that enhance capabilities and efficiency.
• Train entry-level data engineers as directed by department management and mentor junior data engineers on methodologies and optimization techniques.
• Stay current with new technology developments.
• Design and work with complex data models.
• Perform other duties as needed.

Required Qualifications

• Bachelor’s degree (or foreign equivalent) in Computer Science, Computer Engineering, Information Systems, or a related field.
• 5 years of experience in the job offered or related occupations.
• 5 years of experience with ML-based application development and API integration, including building software features that rely on machine-learning models and integrating those models into applications through APIs for automated data and prediction flow; converting research-grade ML models into stable, scalable services accessible to other applications and users; and building and deploying machine learning-based applications, including ML API design and integration.
• 5 years of experience with data engineering and ETL pipelines, including designing automated workflows to extract data from multiple sources, transform it into usable formats, and load it into databases or ML systems; ensuring large volumes of structured and unstructured data are cleaned, validated, and delivered reliably for analytical and machine-learning purposes; and designing and maintaining ETL workflows for large-scale data processing.
• 5 years of experience utilizing database and vector store technologies, including SQL/NoSQL databases and/or vector databases such as Solr, Elasticsearch, or Pinecone.
• 5 years of experience with cloud infrastructure, deployment automation, and containerization, including deploying and operating applications on cloud platforms using automated tools for scalability, consistency, and maintainability; deploying on AWS, Azure, and GCP using infrastructure-as-code tools such as Terraform; and using Docker for containerization.
• 5 years of experience utilizing orchestration tools such as Kubernetes to manage, deploy, and scale containerized applications across multiple servers, supporting availability, fast recovery, and safe rollbacks.
• 5 years of experience with MLOps and model deployment, including deploying ML models using frameworks such as KubeRay, Triton Inference Server, or similar orchestration tools.

Technologies

• ML-Based Application Development, API Integration, machine-learning models
• ETL Pipelines
• Solr, Elasticsearch, Pinecone
• SQL, NoSQL, vector databases
• AWS, Azure, GCP, Terraform, Docker
• Kubernetes
• MLOps, KubeRay, Triton Inference Server
• Agile, Waterfall

Location and Work Model

• Irving, TX (hybrid)

Compensation

• USD 95,300 - 174,600 per year
• U.S. national base pay range: $95,300 - $158,800 (geographic differentials may apply in some locations)
• Salary range for REQ# R119869: $160,285.00 to $174,600.00/year + standard company benefits

Benefits

• Standard company benefits
• Country specific benefits

How to Apply

Send your email to [email protected] and reference job code R119869.