Strong experience architecting enterprise data platforms on Google Cloud (GCP). The architect will work as a strategic technical partner to design and build a GCP Big Query-based Data Lake & Data Warehouse ecosystem.
The role requires deep hands‑on expertise in data ingestion, transformation, modeling, enrichment, and governance, combined with a solid understanding of clinical healthcare data standards, interoperability, and cloud architecture best practices.
Key Responsibilities
1. Data Lake & Data Platform Architecture (GCP)
Architect and design an enterprise‑grade GCP‑based data lakehouse leveraging Big Query, GCS, Dataproc, Dataflow, Pub/Sub, Cloud Composer, and Big Query Omni.
Define data ingestion, hydration, curation, processing and enrichment strategies for large‑scale structured, semi‑structured, and unstructured datasets.
Create data domain models, canonical models,



and consumption‑ready datasets for analytics, AI/ML, and operational data products.
Design federated data layers and self‑service data products for downstream consumers.
Architect batch, near‑real‑time, and streaming ingestion pipelines using GCP Cloud Dataflow, Pub/Sub, and Dataproc.
Set up data ingestion for clinical (EHR/EMR, LIS, RIS/PACS) datasets including HL7, FHIR, CCD, DICOM formats.
Build ingestion pipelines for non‑clinical systems (ERP, HR, payroll, supply chain, finance).
Architect ingestion from medical devices, Io T, remote patient monitoring, and wearables leveraging Io MT patterns.
Manage on‑prem → cloud migration pipelines, hybrid cloud data movement, VPN/Interconnect connectivity, and data

📌 Sr. gcp data engineer (Winnipeg)
🏢 Galent
📍 Winnipeg