Manager, Data Engineering

Odyssey Logistics

Data Engineering Manager leading enterprise data engineering strategy and scalable data solutions at Odyssey Logistics. Managing a team, improving logistics operations through insights and analytics.

Posted 7/29/2026full-timeCharlotte • North Carolina • 🇺🇸 United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in data architecture, data engineering, and cloud platforms, with a strong focus on leading data initiatives that enhance logistics operations and analytics. Proven ability to manage teams and collaborate with stakeholders to deliver high-quality data solutions aligned with business objectives.

Highest-signal resume keywords

Data ArchitectureData EngineeringDatabricksAWSLeadership

ATS Keywords

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Hard Skills

Data ModelingELTETLData GovernanceData QualityPerformance OptimizationScalabilityResilienceAnalyticsBusiness Intelligence

Soft Skills

CollaborationStakeholder ManagementProblem-SolvingCommunicationPrioritization

Tools & Technologies

Delta LakeSigma ComputingSnowflakeAirflowCI/CD

Industry Keywords

LogisticsTransportationSupply ChainGDPRSOX

Tech Stack

Tools & technologies

AirflowAWSCloudETLIoT

About the role

Key responsibilities & impact

Lead the architecture and development of Odyssey’s 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.

Requirements

What you’ll need

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, business intelligence, 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.
Strong collaboration and stakeholder management skills, with the ability to align technical solutions to business needs.
Excellent leadership, problem-solving, communication, and prioritization skills.
Logistics, transportation, or supply chain experience preferred

Benefits

Comp & perks

A choice of medical plans with FSA and HSA options
Dental Insurance
Vision Insurance
Company-paid Life and Disability Insurance
401(k) Plan with Company Match
Paid Time Off (PTO) and Company Holidays
Employee Assistance Program
Company Health & Wellness Program
Discounts with Preferred Vendors