Livingston moves goods across a complex, high-velocity supply chain, and data is at the heart of how we plan, route, and optimize that movement. We're looking for a Senior Data Engineer to design, build, and scale the data infrastructure that powers logistics operations, transportation analytics, warehouse and inventory visibility, and executive decision-making.

Reporting to the Director, IT, this role is a technical anchor within the Data & Analytics function. You'll partner closely with Operations, Supply Chain Planning, Finance, internal IT and Business Intelligence teams to turn high-volume, time-sensitive logistics data into reliable, well-governed and intelligent data products. This is an opportunity to shape data architecture and engineering for a growing organization where data quality and speed directly affect the movement of freight and the customer experience.

Job Duties:

Design, build, and maintain scalable ETL/ELT pipelines that ingest data from transportation management (TMS), ERP, EDI, and telematics/IoT sources.
Architect and optimize data models and data warehouse/lakehouse structures to support reporting, forecasting, advanced analytics and AI.
Build and maintain the infrastructure required to support near-real-time visibility into shipments, inventory, and performance.
Establish and enforce metadata, data quality, validation, and reconciliation processes across high-volume logistics data feeds.
Partner with data analysts, data scientists, and BI developers to ensure data is modeled and delivered in a way that supports self-serve reporting and predictive modeling.
Implement and maintain data governance, lineage, security, and access control practices in line with company policy and regulatory requirements.
Optimize pipeline performance and cost across cloud data platforms, monitoring for reliability, latency, and scalability as data volumes grow.
Collaborate with the Director, IT and cross-functional stakeholders to translate business requirements (e.g., optimization, performance, demand forecasting, Portal integrations, etc.) into technical data solutions.
Provide technical mentorship to junior and intermediate data engineers, and contribute to engineering standards, documentation, and code review practices.
Support the evaluation and integration of new data tools, platforms, and vendor systems.
Participate in on-call rotation and incident response for critical data pipeline issues affecting operational reporting.
Be hands-on with data architecture and engineering functions

Knowledge and skills:

8 years of related experience. Strong proficiency in SQL and other programming languages commonly used in data engineering (e.g., Python, Apache).
Hands-on experience with modern cloud data platforms (e.g., GCP and / or AWS) and associated data services (e.g., Redshift, BigQuery, Composer, Airflow, Knowledge Catalog, BQ Products, BQ Conversational AI).
Experience building and orchestrating pipelines in GCP.
Experience in multiple industries, methodologies and architectures
Strong experience in organizations that have gone / going through technology transformation
Hands-on experience with EDI, APIs, or data integration tools is a strong asset.
Working knowledge of streaming/real-time data technologies (e.g., Kafka, Pub/Sub) is required.
Strong grasp of data governance, security, and privacy best practices.
Excellent communication skills, with the ability to translate technical concepts for non-technical, senior stakeholders.

Sr. Data Engineer

Job description