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Data Engineer
- Toronto, ON, Canada
Contract
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The original listing is kept below for reference.
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- Job type
- Contract
- Closing date
- Posting language
- English
- Posted
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Archived listing. The details below describe a past opening.
Data & Automation Engineer – AI
Location: Toronto, ON | Hybrid
Contract: 12 Months
Experience: 4–7 Years
We are seeking a hands-on Data & Automation Engineer to join our Wealth Client Optimization team, supporting campaign automation, data engineering, cloud modernization, and AI enablement.
Key Responsibilities
- Design and develop scalable data pipelines, integrations, and automated workflows.
- Build solutions using Python, SAS, and SQL for data processing and automation.
- Integrate data and AI/ML model outputs with downstream platforms.
- Develop APIs and workflow orchestration solutions.
- Support SAS-to-cloud migration and modernization initiatives.
- Work with CRM, campaign, fulfillment, and reporting platforms.
- Implement data-quality checks and automated testing.
- Partner with data scientists, analysts, technology teams, and business stakeholders to deliver scalable solutions.
Must-Have Skills
- 4–7 years of relevant Data Engineering / Data Automation experience.
- Strong hands-on Python, SAS, and SQL.
- Experience developing data pipelines, ETL, data integration, and automation.
- Experience with AWS, Azure, GCP, Databricks, or Spark.
- Knowledge of APIs, workflow orchestration, and technical solution design.
- Strong communication and stakeholder management skills.
Nice to Have
- AI/ML model integration
- SAS-to-AWS/cloud migration
- CRM or campaign management platforms
- Data quality and automated testing
- Financial services, banking, or wealth management experience
- Campaign analytics, customer targeting, or client optimization experience
More about this job
Responsibilities
Design and develop scalable data pipelines, integrations, and automated workflows to support campaign automation and AI enablement. Support SAS-to-cloud migration and integrate AI/ML model outputs with downstream platforms.
Requirements
Requires 4-7 years of experience in data engineering and automation with strong proficiency in Python, SAS, and SQL. Experience with cloud platforms like AWS, Azure, or GCP and knowledge of APIs and workflow orchestration is essential.
Skills
- Python
- SAS
- SQL
- Data Pipelines
- ETL
- AWS
- Azure
- GCP
- Databricks
- Spark
- APIs
- Workflow Orchestration
- Data Integration
- Automation
- Stakeholder Management
- Technical Solution Design
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Engineering
- Software
- Finance & Accounting
Keywords
- Data Engineering
- Automation
- AI
- ML
- Python
- SAS
- SQL
- ETL
- AWS
- Azure
- GCP
- Databricks
- Spark
- APIs
- Workflow Orchestration
- Cloud Modernization
- CRM
- Campaign Management
- Financial Services
- Banking
- Wealth Management
- Data Quality
- Automated Testing
- Campaign Analytics
- Customer Targeting
- Client Optimization