Senior Data Engineer II

Posted Yesterday
Be an Early Applicant
Irving, TX, USA
In-Office
95K-175K Annually
Senior level
Information Technology • Legal Tech • Analytics
The Role
Develop and maintain complex data engineering solutions, including daily data loads, ETL pipelines, data models, ML-based applications, APIs, cloud deployments, containerized services, and MLOps workflows. Responsibilities include coding, debugging, requirements analysis, design, process improvement, code reviews, Agile and Waterfall collaboration, and mentoring junior data engineers.
Summary Generated by Built In

  • RELX Inc. d/b/a LexisNexis USA
  • Senior Data Engineer II 
  • 400 East Las Colinas Blvd., Irving, TX 75039

JOB DESCRIPTION:

  • Perform daily data loads, ensuring recurring updates are logged and tracked. Interface with other technical personnel or team members to document, interpret and finalize requirements. Produce code that is efficient, repeatable, without defects, and adherent to best practices such as naming conventions, and encapsulation. Write and review portions of detailed specifications for the development of system components of moderate complexity. Complete complex data engineering bug fixes and resolve related issues, researching and identifying root causes as appropriate. Work closely with other development team members to understand complex product requirements and translate them into data engineering and/or data management designs. Innovate process improvements that enable efficient delivery and maintenance. Successfully implement development processes, coding best practices, and code reviews. Operate in various development environments (including Agile and Waterfall) while collaborating with key stakeholders. Identify areas where it is an advantage to work with other teams to improve overall quality, and with peers or others, implement initiatives improving capabilities and efficiency. Train entry-level data engineers as directed by department management, ensuring they are knowledgeable in critical aspects of their roles, and mentor junior data engineers on methodologies and optimization techniques. Keep abreast of new technology developments. Design and work with complex data models. Perform other duties as needed.

REQUIREMENTS:

  • Bachelor’s degree (or foreign equivalent) in Computer Science, Computer Engineering, Information Systems, or a related field required.
  • 5 years of experience in job offered or related occupations required.
  • Also required is: 5 years of experience: with ML-Based Application Development & API Integration to build software features that rely on machine-learning models and to integrate those models into applications through APIs so the system can send data and receive predictions automatically; convert research-grade ML models into stable, scalable services that other applications and users can access reliably; building and deploying machine learning-based applications, including the design and integration of ML APIs and RESTful for scalable, production-grade systems; with data engineering & ETL Pipelines to design automated workflows that extract data from multiple sources, transform it into usable formats, and load it into databases or ML systems, ensuring that large volumes of structured and unstructured data are cleaned, validated, and delivered reliably for analytical and machine-learning purposes; designing and maintaining ETL workflows for large-scale data processing, including structured and unstructured data; utilizing database & Vector Store Technologies; using SQL/NoSQL databases and/or vector databases such as Solr, Elasticsearch, or Pinecone; with Cloud Infrastructure, Deployment Automation & Containerization to deploy and operate applications on cloud platforms using automated tools to ensure systems are scalable, consistent, and easy to maintain; deploying applications on cloud platforms including AWS, Azure, and GCP, using infrastructure-as-code tools such as Terraform, and containerization technologies including Docker; utilizing orchestration tools such as Kubernetes to automatically manage, deploy, and scale containerized applications across multiple servers to ensure applications remain available, recover quickly from failures, and can be updated or rolled back safely without interrupting service; with MLOps & Model Deployment; and with MLOps practices and deploying ML models using frameworks such as KubeRay, Triton Inference Server, or similar orchestration tools.
  • Employee reports to RELX, Inc. d/b/a LexisNexis USA office in Irving, TX, but may telecommute from any location within the U.S.
  • Experience can be concurrent.

SALARY RANGE FOR REQ# R119869:

  • $160,285.00 to $174,600.00/year + standard company benefits
  • This salary range is specifically for REQ# R119869. Salary range listed below is general and covers all similar positions in the area and should not be considered for this specific position.

 

HOW TO APPLY:

  • Interested candidates should send email to [email protected] and reference job code: R119869

#LI-DNI

#IND-DNS

#ICT



U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates.

We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.

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We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.

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Skills Required

  • Bachelor's degree or foreign equivalent in Computer Science, Computer Engineering, Information Systems, or a related field
  • Five years of experience in the job offered or related occupations
  • Five years of experience with ML-based application development and API integration
  • Five years of experience converting machine-learning models into stable, scalable services
  • Five years of experience building and deploying machine-learning applications using ML APIs and REST APIs
  • Five years of experience designing and maintaining data engineering and ETL pipelines for structured and unstructured data
  • Experience utilizing SQL, NoSQL, and/or vector databases such as Solr, Elasticsearch, or Pinecone
  • Experience deploying applications on AWS, Azure, and/or Google Cloud Platform
  • Experience with infrastructure-as-code tools such as Terraform
  • Experience with containerization technologies including Docker
  • Experience with Kubernetes orchestration
  • Experience with MLOps and machine-learning model deployment
  • Experience deploying machine-learning models using KubeRay, Triton Inference Server, or similar orchestration tools

RELX Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about RELX and has not been reviewed or approved by RELX.

  • Retirement Support — Retirement support is positioned as a meaningful part of total rewards through a 401(k) plan with matching contributions, alongside other financial protections such as life and disability coverage. Tuition reimbursement and share purchase access further broaden the financial value of the package beyond base salary.
  • Leave & Time Off Breadth — Leave and time off breadth appears strong, with generous vacation allowances, mental health days, and options like sabbaticals and tiered PTO by tenure. Parental and caregiving leaves are described in detail, reinforcing time-away benefits as a standout component of the overall package.
  • Wellbeing & Lifestyle Benefits — Wellbeing and lifestyle benefits are supported by offerings such as mental health support (e.g., app access), EAP resources, gym-related perks, and wellness incentives. Flexible working hours and related work-life supports add to the perceived day-to-day value of benefits.

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The Company
HQ: London
10,001 Employees
Year Founded: 1880

What We Do

RELX is a global provider of information-based analytics for professional and business customers across industries. We help scientists make new discoveries, doctors and nurses improve the lives of patients and lawyers win cases. We prevent online fraud and money laundering, and help insurance companies evaluate and predict risk. Our events enable customers to learn about markets, source products and complete transactions. In short, we enable our customers to make better decisions, get better results and be more productive. We do this by leveraging a deep understanding of our customers to create innovative solutions which combine content and data with analytics and technology in global platforms. RELX serves customers in more than 180 countries and has offices in about 40 countries. It employs approximately 30,000 people of whom almost half are in North America. We operate in four major market segments: Scientific, Technical & Medical; Risk & Business Analytics; Legal; and Exhibitions.

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