Job Title: Data Engineer

Vacancies: This posting is for (1) current vacancies

Location: Toronto, ON | Vancouver, BC | Ottawa, ON | Calgary, AB | Halifax, NS | St John's, NL | Kelowna, BC| Prince George, BC | Montreal, QC | Québec, QC (Detailed office location information can be found by visiting this link: https://cancer.ca/en/contact-us)

Work Model: Hybrid Work Model

Salary Band: 5 ($83,000 - $93,000 CAD)

HELP SHAPE THE FUTURE OF CANCER CARE IN CANADA

The Canadian Cancer Society works tirelessly to save lives, improve lives and drive collective action against cancer. Together with patients, volunteers, donors and communities across the country, we raise funds to invest in transformative cancer research, we provide a caring support system for everyone affected by cancer and we advocate to governments to create a healthier future for all. It takes a society to take on cancer – and the Canadian Cancer Society is leading the way

MAKING AN IMPACT

Reporting to the Senior Manager, Data Engineering & Services, the Data Engineer is involved in designing, developing, maintaining and optimizing data platform services, meta-data driven data pipelines and data solutions using the organization’s data platforms and technologies.

- Deliver scalable, automated, and maintainable data pipelines, integrations, and services using modern cloud technologies and platforms.
- Partner with business and technical teams to design and implement data solutions that adhere to security best practices and align with data governance standards.
- Support a data-driven,



innovation-focused engineering setting by applying modern design patterns and leveraging emerging technologies to improve how data is integrated, governed, and utilized across the organization.

What You’ll Be Doing

- Data Engineering & Platform Development

Data Pipelines

- Design, implement, and optimize data ingestion and transformation processes using Microsoft Fabric (Data Pipelines, Dataflows, and Notebooks)
- Develop end-to-end ETL/ELT workflows for structured and unstructured data
- Automate and orchestrate data workflows for efficiency and reliability

Data Lakehouse

- Implement Data Lakehouse architecture leveraging modern data standards
- Design and optimize data models using medallion architecture
- Optimize storage and processing solutions for performance and cost-effectiveness

Data Transformation

- Develop data transformations using Apache Spark in Fabric Notebooks for cleansing, aggregation, and enrichment
- Optimize Spark workloads, queries, and configurations for performance tuning
- Support legacy data platforms and integration processes as required

Data Analytics

- Build reusable, high-quality datasets and data assets for reporting and insights

Integrations & Data Pipelines

Data Workflows

- Develop and maintain data integrations with Azure data services, external systems, and reporting platforms
- Implement data ingestion processes across batch and real-time workflows




- Develop transformation framework to support data movement and processing across systems
- Automate data workflows and integration processes to improve efficiency and reliability

Collaboration And Documentation

- Coordinate with business and technical teams to translate integration requirements into scalable data solutions
- Support data consistency and relationships across systems through integration and data processing workflows
- Develop and maintain integration documentation, including data mappings and data models

DevOps & Support

Build And Release Management

- Develop and maintain CI/CD pipelines using Azure DevOps for data platform solutions
- Support source control, branching strategies, and automated deployment processes
- Contribute to infrastructure as code, orchestration, and deployment of data pipelines and services

Operations And Reliability

- Implement monitoring, logging, and alerting for data pipelines and integrations
- Support performance optimization and operational reliability of data solutions
- Support data lifecycle processes including archiving, backup, and replication across key platforms
- Participate in Agile development processes, including sprint planning and iterative delivery

Data Governance & Quality

Governance And Security

- Apply data governance, compliance, and data quality standards when developing and delivering data pipelines and integrations
- Support lineage and metadata management using tools such as Microsoft Purview
- Implement and support data security controls aligned with organizational compliance standards

📌 Data Engineer (St. John's)
🏢 Canadian Cancer Society
📍 St. John's