Data Engineering Lead

Remitly-posted 18 days ago

Full-time • Manager

Raleigh, NC

1,001-5,000 employees

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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.

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.

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.
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.
Leadership Qualifications 2+ years of experience managing or leading engineering teams (people management preferred).
Proven ability to build strong engineering culture, drive accountability, and grow talent.
Strong communication skills with the ability to align stakeholders across product, architecture, and engineering.
Experience 8+ years in Data Engineering, Platform Engineering, or relevant data-heavy engineering roles.
Education Bachelor’s Degree (Engineering/Computer Science preferred but not required); or equivalent experience required.
Experience delivering solutions in large-scale, high-compliance enterprise environments.
Experience working with structured, semi-structured, and unstructured data.

Databricks - experience processing large datasets using Spark and Delta Lake.
Matomo - exposure to tracking/analytics data ingestion and event pipelines.
FullStory - 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 cataloging, lineage, and governance frameworks.
API integration & event streaming - Kafka, Kinesis, or similar tools is a plus.

We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer to our US full- and part-time employees working at least 20 hours or more per week:
Health Benefits: Comprehensive, multi-carrier program for medical, dental and vision benefits
Retirement Benefits: 401(k) with match and an Employee Share Purchase Plan
Wellbeing: Wellness platform with incentives, Headspace app subscription, Employee Assistance and Time-off Programs
Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital Indemnity
Family Benefits, including bonding and family care leaves, adoption and surrogacy benefits
Health Savings, Health Care, Dependent Care and Commuter Spending Accounts
In addition to annual Paid Time Off, we offer up to two days of paid leave each to participate in Employee Resource Groups and to volunteer with your charity of choice

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