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, and executive decision-making. The ideal candidate must have experience in building end-to-end data pipelines in GCP.
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:
- 6 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.
