Data Engineer

Location: Timiskaming North (Iroquois Falls A)

The Data Engineer provides critical support for the organization’s data infrastructure, specifically focusing on building and maintaining a unified data management platform. The incumbent will own the hospital’s underlying data foundation, transforming raw inputs into analytics‑ready, AI‑ready, highly reliable data structures that empower decision support, mandated reporting, research enablement, and regional clinical partnerships.

The role functions as the primary architect and operator of the entire data pipeline, directly addressing the technical bottlenecks of data ingestion, ETL (Extract, Transform, Load), Lakehouse management, and overall pipeline reliability. Working collaboratively with Decision Support Advisors, clinical leadership, IS/IT, and regional partners, the Data Engineer builds the sound, governed, well‑modelled data foundation necessary to make advanced analytics and future artificial intelligence initiatives trustworthy, scalable, and secure.

July 17, 2026

Position Responsibilities

Under the general direction of the Vice‑President Corporate / Chief Financial Officer (CFO).

Design, build, and operate the entire data pipeline and unified data management platform utilizing Microsoft Fabric, data lakes, and data warehouses.

Own and manage data ingestion processes from various sources, including the ONEHITS Data Repository (Meditech Expanse DR), MED
2020, Ministry data, spreadsheets, and other internal/external systems.

Develop, optimise, and maintain complex SQL scripts and ETL/ELT workflows to clean, transform, and structure raw data into meaningful, curated datasets.

Curate, model, and maintain semantic models (“Golden datasets”) that reliably feed Power BI dashboards and all downstream clinical and operational analytics.

Ensure the stability, scalability, and reliability of Lakehouse architectures and automated data pipelines.

Build a robust, governed, and accurate data foundation required to safely adopt and implement future Artificial Intelligence (AI) solutions in a healthcare setting.

Implement data‑quality tools and automated monitoring to assist clinical staff in capturing clean, reliable data at the source.

Collaborate with Decision Support Advisors to offload data engineering constraints, allowing them to focus on clinical partnerships and high‑value analytical workflows.

Support the data infrastructure needed for mandatory reporting (MoH, Ontario Health, OHA), Ministry stats integrity (OHRS rules/Trial Balance submissions), and research enablement.

Support the expansion of data analytics services and pipeline architecture to encompass regional peers and cluster hospitals under service agreements.

Collaborate with internal stakeholders, IT, privacy leadership, and external partners to ensure data architecture adheres to structural, security, and privacy best practices.

Establish and maintain comprehensive documentation for all institutional data pipelines, architectures, and semantic models.

Fine‑tune SQL queries, stored procedures, and Fabric capacities to handle high volumes of longitudinal patient data while managing compute costs (F‑SKUs).

Position Requirements
EDUCATION AND TRAINING:

Undergraduate degree in Computer Science, Data Engineering, Software Engineering, Health Informatics, or a highly related technical field.

Equivalent combinations of education and experience may be considered.

Certifications in Microsoft Fabric Analytics Engineering, Azure Data Engineering, or related Microsoft data platform credentials are a strong asset.

Demonstrated ability to architect secure data platforms and interpret data governance policies and precedents.

EXPERIENCE:

Minimum of five (5) years of experience in data engineering within an Ontario healthcare setting.

Extensive hands‑on experience designing and managing data solutions, including Lake houses, data warehouses, and data lakes.

Extensive experience building and maintaining robust ETL/ELT pipelines and writing complex SQL scripts for data transformation.

Experience extracting and engineering data from specific healthcare systems such as Meditech Expanse, MED
2020, and provincial data repositories.

Experience curating semantic models for…