LexisNexis Legal & Professional is a leading global provider of legal, regulatory and business information and analytics that help customers increase productivity, improve decision-making and outcomes, and advance the rule of law around the world. As a digital pioneer, the company was the first to bring legal and business information online with its Lexis® ...
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This role supports Global Operations by designing, building, and maintaining reliable data pipelines and platforms. You will enable high‑quality analytics and AI‑ready data while improving automation, performance, and scalability. The role involves close collaboration with technical and business partners and encourages the responsible use of AI‑assisted engineering practices.
Key Responsibilities
Design, build, and maintain scalable data pipelines and integrations that support analytics and AI use cases.
Develop high‑quality, well‑tested code that follows best practices for readability, security, and maintainability.
Use SQL as a primary tool to query, transform, validate, and optimize data across systems.
Collaborate with technical and business partners to understand data needs and translate them into practical data solutions.
Document data requirements and contribute to specifications for analytics and AI‑enabled workflows.
Troubleshoot and resolve data issues through root cause analysis and appropriate automation or tooling.
Identify opportunities to improve efficiency through automation, orchestration, or AI‑assisted processes.
Participate in code reviews and development processes that promote reproducibility, transparency, and data quality.
Support database and data flow management to ensure systems meet organizational standards for reliability and AI readiness.
Stay current with evolving data engineering, automation, and AI practices and apply relevant learnings to your work.
Required Skills and Experience
Professional experience in data engineering, data management, or a related technical role.
Strong, hands‑on SQL expertise required, including writing complex queries, performance tuning, and data validation.
Experience with data modeling, file management, and data transformation workflows.
Working knowledge of at least one additional programming or scripting language (such as Python, Java, or similar).
Experience with databases, data platforms, or cloud services (for example, AWS, Azure, GCP, Redshift, or Teradata).
Familiarity with version control, testing, and core software development practices.
Strong problem‑solving skills and clear, collaborative communication.
Experience with ETL/ELT processes or general workflow orchestration concepts.
Exposure to AI, machine learning, or data automation tools and practices.
Experience with data visualization tools (such as Tableau or similar).
A bachelor’s degree in a related field or equivalent practical experience. We welcome candidates from non‑traditional educational and career paths.
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