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® ...
Read more about this company
As a Senior Software Engineer, you will lead the design, development, and operation of scalable data platforms, services, and infrastructure that power critical business outcomes. Working closely with analysts, data scientists, and engineers, you will drive technical excellence, mentor team members, and help shape the future direction of the Data Engineering function. This role offers the opportunity to combine strong engineering fundamentals with AI-assisted development practices to deliver reliable, high-impact solutions.
Responsibilities
Lead the design, build, and maintenance of data pipelines and backend services using Python
Write efficient, well-structured SQL for data extraction, transformation, and analysis, and set standards for query and schema design across the team
Develop and maintain APIs and services (e.g. using FastAPI and SQLAlchemy) to expose data to internal and external consumers
Own technical design decisions for data systems, balancing scalability, reliability, and maintainability
Collaborate with data analysts, scientists, and other engineers to understand data needs and deliver reliable solutions
Drive the design and upkeep of infrastructure supporting data workloads (containers, orchestration, provisioning)
Monitor, troubleshoot, and improve the performance and reliability of existing data systems, including leading incident response and root-cause analysis where needed
Mentor other engineers, lead code reviews, and help raise the technical bar across the team
Requirements
Deep proficiency in Python for building applications, pipelines, or services at scale
Strong SQL skills, writing performant queries, designing schemas, and optimizing for large or complex datasets
Significant experience working in a data engineering or backend engineering environment, including owning systems end-to-end
Demonstrated ability to make sound architectural and technical trade-off decisions
Experience mentoring engineers and/or leading technical initiatives
Comfort working in a fast-paced, collaborative team setting
Experience developing and maintaining APIs and services
Experience working with AI-assisted development tools and supporting team adoption of AI capabilities
20 Initiatives to Boost Employee EngagementAre you struggling with improving employee engagement at work? This article covers everything from better communication to building a strong workplace culture.
30 Common Interview Mistakes to AvoidThis piece examines 30 of the most common mistakes applicants make at interviews, so you know how to better avoid them.
Gmail
Yahoomail