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.
Requirements
- Python - strong hands-on experience writing production-grade code for ETL/ELT and automation.
- SQL - expert-level ability to write, optimize, and troubleshoot complex SQL queries at scale.
- AWS - strong experience with cloud data services such as S3, Redshift, Lambda, Glue, EMR, Step Functions, IAM, etc.
- Redshift - hands-on experience modeling data, optimizing queries, and managing Redshift clusters.
- DevOps - knowledge of CI/CD pipelines, GitOps, automation, monitoring, environment management, and infrastructure-as-code.
- Orchestration - experience with Airflow, Step Functions, or equivalent workflow orchestration tools.
- Databricks - experience processing large datasets using Spark and Delta Lake.
Responsibilities
- 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.
- 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.
Other
- 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.
- 2+ years of experience managing or leading engineering teams (people management preferred).
