Data Engineering Lead Raleigh, NC

Position: Data Engineering Lead at Disability Solutions Raleigh, NC

Data Engineering Lead job at Disability Solutions. Raleigh, NC. Lexis Nexis 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 Lexis Nexis 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.

Technical Skills & Experience Required Technical Skills

• 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.
• Dev Ops - knowledge of CI/CD pipelines, Git Ops, automation, monitoring, environment management, and infrastructure-as-code.
• Orchestration - experience with Airflow, Step Functions, or equivalent workflow orchestration tools.

Preferred / Nice-to-Have Skills

• Databricks - experience processing large datasets using Spark and Delta Lake.
• Matomo - exposure to tracking/analytics data ingestion and event pipelines.
• Full Story - experience handling behavioral analytics, session replay data, or similar tools.
• Pendo - experience with product analytics datasets and event telemetry.
• EMR - experience running distributed data processing workloads using Hadoop/Spark on AWS EMR.
• Data Quality & Governance - familiarity with…