Global Logistics Data Engineering Lead

CRG

Charlotte (NC)

On-site

USD 140,000 - 180,000

Full time

14 days+

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Job summary

CRG, a global logistics leader, seeks a Data Engineering Lead in Charlotte, NC to drive enterprise data strategy, platform development, and scalable data solutions for operations, analytics, and AI-enabled decision making.

You will lead a global team, own the modern data stack (Databricks, Delta Lake, Snowflake, Airflow, AWS), oversee ELT/ETL pipelines from TMS/WMS/IoT, and partner with business stakeholders to translate logistics challenges into trusted data products.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field.
5+ years of experience building and supporting data platforms, analytics, BI, or data engineering solutions.
2+ years of leadership and management experience.
Strong technical expertise in data architecture, data modeling, cloud platforms, and modern data engineering practices.
Experience with Databricks, AWS, Snowflake, Airflow, Sigma Computing, or comparable tools and platforms.
Proven ability to lead large-scale data initiatives that support business goals and improve decision-making.

Responsibilities

Lead the architecture and development of the enterprise data lake to improve logistics operations, real-time tracking, supply chain optimization, and customer-facing analytics.
Partner with business, operations, and product stakeholders to identify high-impact data initiatives, prioritize delivery, and translate logistics use cases into scalable technical solutions.
Own and evolve the modern data stack, including Databricks, Delta Lake, Sigma Computing, Snowflake, Airflow, and AWS.
Oversee ELT/ETL pipelines integrating data from TMS, WMS, telematics, EDI feeds, and IoT sensors.
Deliver trusted, reusable, high-quality data products that support self-service dashboards, operational reporting, and embedded analytics.
Implement best practices for data observability, pipeline orchestration, CI/CD, performance optimization, scalability, and resilience.
Champion data governance, lineage, and quality standards aligned with GDPR, SOX, customer SLAs, and internal standards.
Manage sprint planning, agile execution, resource allocation, and team development.
Collaborate with vendors and external partners on tool adoption, integrations, and roadmap alignment.
Lead, coach, develop, and retain a high-performing global data engineering team.