Data Engineer

St. Joseph's Healthcare Hamilton•Hamilton, ON

3d•CA$56 - CA$64•Hybrid

About The Position

The Data Engineer provides technical leadership in the design, development, and operation of St. Joseph’s enterprise data platforms, data pipelines, data models, and analytics engineering practices. This role is responsible for building and optimizing the organization’s modern data ecosystem, including ingestion, processing, quality, governance integrations, and performance optimization, in alignment with SJHS’s Enterprise Data Strategy. The Data Engineer will leverage deep expertise in modern data engineering technologies, frameworks, and methodologies to deliver scalable, reliable, and secure data solutions. The role collaborates closely with clinical, operational, and technical stakeholders to ensure data systems meet organizational needs for analytics, reporting, interoperability, and compliance.

Requirements

Technical leadership in the design, development, and operation of enterprise data platforms, data pipelines, data models, and analytics engineering practices.
Building and optimizing the organization’s modern data ecosystem, including ingestion, processing, quality, governance integrations, and performance optimization.
Leveraging deep expertise in modern data engineering technologies, frameworks, and methodologies to deliver scalable, reliable, and secure data solutions.
Collaborating closely with clinical, operational, and technical stakeholders to ensure data systems meet organizational needs for analytics, reporting, interoperability, and compliance.
Experience with Microsoft Fabric and Epic.
Familiarity with ETL development, orchestration, monitoring, and operational support.
Experience developing reusable assets such as pipeline templates, transformation frameworks, connectors, and modular data models.
Evaluating and introducing modern data engineering tools and technologies.
Designing and implementing high‑performance data models supporting reports, dashboards, applications, and analytic workloads.
Developing robust data endpoints and optimized data products for downstream user and system consumption.
Supporting self-serve analytics by engineering high‑quality, well-documented datasets and promoting data literacy across the organization.

Nice To Haves

St. Joseph’s Healthcare Hamilton (SJHH) is an equal opportunity employer and strives for equity, inclusiveness, and diversity in all our programs, practices, facilities, and people.
We foster a culture of patient and staff safety where all positions comply and work in conjunction with the Mission, Vision, and Core Values of SJHH.
SJHH is committed to a barrier-free recruitment and selection process - please inform us should accommodation be required at any point in the recruitment process.
At St. Joe’s Hamilton, we believe in nurturing new talent, providing an inclusive and supportive work environment with meaningful growth opportunities, and exciting benefits and rewards.
Whether you're passionate about providing compassionate care or eager to gain new skills, there’s a place here for you to grow, learn, and succeed!

Responsibilities

Implementation St. Joseph’s modern data and analytics platform, ensuring scalability, reliability, and performance.
Design, develop, and maintain enterprise-grade data pipelines (batch/stream), ingestion frameworks, and integration patterns.
Build and maintain core data models, curated datasets, and semantic layers supporting analytics, BI, and advanced use cases in applications including Microsoft Fabric and Epic.
Partner with other Data Analytics, clinical, and operational teams to translate data requirements into robust engineering solutions.
Develop the data engineering framework including toolsets, source control practices, testing standards, and documentation.
Establish and enforce best practices for ETL development, orchestration, monitoring, and operational support.
Develop reusable assets such as pipeline templates, transformation frameworks, connectors, and modular data models.
Proactively evaluate and introduce modern data engineering tools and technologies, ensuring alignment with strategic goals.
Design and implement high‑performance data models supporting reports, dashboards, applications, and analytic workloads.
Develop robust data endpoints and optimized data products for downstream user and system consumption.
Support self-serve analytics by engineering high‑quality, well-documented datasets and promoting data literacy across the organization.