Sr. Data Engineer

Livingston International; Toronto; On-site; CAD 110,000 - 170,000; Full time

Job summary

Livingston International seeks a Senior Data Engineer to design, build, and scale data infrastructure powering logistics analytics and decision-making. You will partner with Operations, Supply Chain Planning, Finance, and BI teams to deliver reliable data products and self-serve reporting.

You will shape data architecture for a high-velocity supply chain, ensure data quality, and drive governance across diverse data feeds while mentoring junior engineers.

Qualifications

• 8+ years of related experience in data engineering.
• Strong proficiency in SQL and Python; experience with Apache.
• Experience building ETL/ELT pipelines and data modeling for analytics.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines for TMS/ERP/EDI/IoT data.
• Architect data models and lakehouse structures for reporting and AI.
• Maintain near-real-time visibility into shipments and inventory.
• Enforce data governance, quality, and security practices.

Skills

SQL

Python

Apache

Data engineering

Tools

Redshift

BigQuery

Composer

Airflow

Knowledge Catalog

BQ Products

BQ Conversational AI

Kafka

Pub/Sub

Job description

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.