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Added 24 mins ago
Project Manager, Construction and Store Development
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ON
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Added 53 mins ago
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- Full-time
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VP, Business Development - Canada
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- Full-time
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Civil Engineering Lead
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Senior Developer
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Livingston International

Senior Data Engineer

Toronto, ON, M9C 5J5, Canada

The good-faith salary range for this position is 84,455-115,000 USD. · Full-time

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Job details

Pay: The good-faith salary range for this position is 84,455-115,000 USD.
Job type: Full-time
Apply by: Nov 22, 2026
Posting language: English
Posted: Sep 23, 2026

Original job description

Senior Data Engineer

Join Livingston and grow your career in the constantly changing world of international trade. Livingston is a market leader offering customs brokerage, international trade consulting, compliance and freight forwarding services around the world. Livingston has over 3,000 employees at more than 90 key border crossings, sea ports, airports and other strategic locations in North America, Europe and Asia.

Our fast-paced and collaborative environment offers you the opportunity to work with leaders in the industry, receive recognition for achievements and develop your expertise in the complex and evolving world of trade. Learn how you can make an impact at Livingston.

JOB SUMMARY

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 senior 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.

KEY DUTIES & RESPONSIBILITIES

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 & SKILLS

To perform this job successfully, the person must be able to perform each essential duty satisfactorily. The requirements listed below are representative of the knowledge, skills, and abilities required. Reasonable accommodations may be made to enable a person with disabilities to perform the essential functions.

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.

WORK EXPERIENCE – MINIMUM REQUIRED

EDUCATION

Required: Bachelors Degree or equivalent in Computer Science

CERTIFICATIONS DESCRIPTION

Certifications in GCP, Data Architecture and Data Engineering
Preferred certifications in AI and CICD

At Livingston, we are committed to fostering a flexible, growth-oriented environment where you can thrive. Our culture is built on respect, recognition, and collaboration, and we empower our team with trusted expertise, continuous learning opportunities, and long-term support. We offer competitive compensation, comprehensive benefits, and a transparent pay philosophy aligned with market data and job-related factors.

Base salary is one component of our total rewards package which also includes incentive opportunities, benefits, and professional development. Salary ranges are established by location and reflect relevant factors such as skills, experience, and market conditions. The good-faith salary range for this position is 84,455-115,000 USD. Actual compensation will be determined based on these factors and may vary accordingly.

Diversity, Equity, and Inclusion at Livingston

We are proud to be an inclusive employer and welcome applications from individuals of all backgrounds, experiences, and perspectives. Inclusiveness makes us stronger and better at what we do. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.

Livingston is an equal opportunity employer and committed to creating and sustaining an inclusive environment in which all individuals are treated with dignity, respect and one which reflects the diversity of the community in which we operate. Accommodations are available for applicants and employees with disabilities throughout the recruitment process. If you require accommodations for interviews or other meetings, please advise when submitting your application.

Job Type: Full Time

Location: ON Toronto - CN030

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More about this job

Responsibilities

The Senior Data Engineer will design, build, and scale data infrastructure to support logistics operations and executive decision-making. They will also manage ETL/ELT pipelines and ensure data quality, governance, and security across high-volume logistics data feeds.

Requirements

Candidates must have a Bachelor's degree in Computer Science and strong proficiency in SQL, Python, and cloud data platforms like GCP or AWS. Experience with data modeling, streaming technologies, and data governance in a professional environment is required.

Skills

SQL
Python
Apache
GCP
AWS
Redshift
BigQuery
Airflow
Data modeling
ETL/ELT pipelines
Data governance
Kafka
Pub/Sub
Logistics data
API integration
Data architecture

Benefits

Competitive compensation
Comprehensive benefits
Professional development
Incentive opportunities

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
SQL
Python
GCP
AWS
Redshift
BigQuery
Airflow
ETL
ELT
Data Warehouse
Lakehouse
Kafka
Pub/Sub
Logistics
Supply Chain
Data Governance
Data Modeling
API
EDI
Telematics
IoT
Data Quality
Cloud Computing
Data Architecture
Predictive Modeling
Business Intelligence
Data Security
Infrastructure
Analytics

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