LexisNexis is seeking an experienced Data Engineering Lead LexisNexis is seeking an experienced Data Engineering Lead to manage and develop a high-performing engineering team that delivers secure, scalable, and business-critical data solutions across our global platforms. This role requires a strong people manager with hands-on technical expertise and the ability to lead teams through complex data engineering challenges in a fast-paced, enterprise environment. You will manage a team that includes Consulting Data Engineers, Senior Data Engineers, Data Engineers III, Data Engineer II and entry-level engineers, guiding their growth and ensuring strong execution, delivery quality, and engineering excellence. This is a leadership role for someone who can balance team management, delivery ownership, and architectural oversight-while maintaining a strong technical foundation. What You’ll Do People Leadership & Team Management Lead, mentor, and manage a multi-level data engineering team (Consulting, Senior, DE III/II/I) distributed across multiple global locations. Drive career development, skill growth, coaching, and performance reviews for all team members. Build an inclusive, collaborative, and high-accountability team culture aligned with LexisNexis values. Participate in hiring, onboarding, and talent planning to strengthen the engineering organization. Delivery & Execution Ownership Own execution and delivery of all data engineering roadmap items for your domain. Manage sprint planning, prioritization, estimation, and work allocation across multiple projects. Track delivery KPIs-pipeline availability, data quality, SLA adherence, velocity, and stability. Anticipate risks, resolve blockers, and ensure consistent, predictable delivery. Technical Leadership & Architectural Oversight Provide architectural guidance on building secure, scalable cloud data pipelines and platforms. Ensure all solutions meet enterprise standards for governance, observability, and compliance. Review and approve solution designs, architectural documents, and critical code paths. Guide the team in implementing best practices in CI/CD, testing, modularity, resiliency, and documentation. Cross-Functional Collaboration Partner with Product, Architecture, Platform Engineering, Data Governance, and business teams. Translate business requirements into actionable engineering tasks and technical designs. Influence upstream and downstream teams to ensure data consistency, quality, and availability. Represent the Data Engineering function in planning meetings, architecture reviews, and operational forums. Operational Excellence Oversee production data pipelines, ensuring reliability, cost efficiency, and optimal performance. Implement best practices for monitoring, logging, alerting, on-call rotations, incident management, and RCA. Drive automation across deployment, testing, orchestration, and environment provisioning. Continuously reduce technical debt and enhance platform scalability and resilience.