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Insight Global

Data Engineer

Toronto, ON, Canada

$60 to $80 CAD / hour · Contract

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Job details

Pay: $60 to $80 CAD / hour
Job type: Contract
Apply by: Nov 25, 2026
Experience: 3+ years of Data Engineering experience
Posting language: English
Posted: Oct 26, 2026

Original job description

Required Skills & Experience

Strong Python development experience.

Advanced SQL skills.

3+ years of Data Engineering experience

Hands-on experience developing and migrating data pipelines.

Proven experience migrating data/workloads from on-premises environments to AWS.

Strong hands-on experience working within the AWS ecosystem.

Experience integrating and transforming data from multiple sources.

Strong communication and stakeholder-management skills.

Ability to operate in a consultative capacity, working directly with the business. Experience working within a large enterprise environment.

Nice to Have Skills & Experience

Banking / FS experience

Commercial Banking

Job Description

We are seeking a Data Engineer to support a large enterprise transformation focused on building data pipelines, integrating data, and migrating data workloads from on-premises environments to AWS. This person should be technically strong in Python and SQL, have hands-on AWS migration experience, and be comfortable partnering directly with business stakeholders. Experience with Machine Learning and MLOps is a strong plus, particularly supporting models through integration and production environments. The scope of work will be contributing to Commercial Banking's Underwriting AI enablement/automation vision

Key Responsibilities

Design, develop, and maintain data pipelines.

Migrate existing data pipelines and workloads from on-premises infrastructure to AWS.

Gather, integrate, transform, and prepare data from multiple sources.

Use Python and SQL extensively for data development and manipulation.

Support integration of data into existing enterprise platforms and applications.

Partner with business and technical stakeholders to understand requirements and translate them into technical solutions.

Support ML/MLOps integration into production environments where applicable.

Work within an enterprise environment supporting business-critical applications and workflows.

Communicate technical concepts clearly to both technical and non-technical stakeholders.

Artificial intelligence tools are used to assist in screening and assessing applicants for this position.

Vacancy: This posting is for a currently vacant role, and the successful candidate will be hired into an existing open position.

60-80/hr

Apply About employer

More about this job

Responsibilities

Design, develop, and maintain data pipelines, including migrating existing pipelines and workloads from on-premises infrastructure to AWS. Integrate and prepare data from multiple sources, support enterprise platform and ML/MLOps integrations, and collaborate with business and technical stakeholders to deliver solutions for Commercial Banking underwriting automation.

Requirements

Requires strong Python and advanced SQL skills, at least three years of data engineering experience, hands-on pipeline development and migration experience, and practical experience migrating workloads from on-premises environments to AWS. Candidates should also have experience integrating data from multiple sources, working in large enterprises, and communicating effectively with business stakeholders; banking or financial services experience and ML/MLOps are preferred.

Skills

Python
Advanced SQL
Data Engineering
Data Pipeline Development
Data Migration
AWS
Data Integration
Data Transformation
Stakeholder Management
Business Communication
Machine Learning
MLOps
Enterprise Data Platforms
Commercial Banking

Visa sponsorship

Not detected in the job text

Keywords

Python
SQL
Data Engineering
Data Pipelines
AWS
Cloud Migration
On-Premises Infrastructure
Data Workloads
Data Integration
Data Transformation
Enterprise Platforms
Machine Learning
MLOps
Production Environments
Commercial Banking
Underwriting
AI Enablement
Automation
Stakeholder Management
Business-Critical Applications

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