Sr. GCP Data Engineer in Winnipeg

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 BigQuery-based Data Lake & Data Warehouse ecosystem. The role requires deep hands-on expertise in data ingestion, transformation, modeling, enrichment, and governance, combined with a strong understanding of clinical healthcare data standards, interoperability, and cloud architecture best practices.

Key Responsibilities

• Data Lake & Data Platform Architecture (GCP)
  • Architect and design an enterprise-grade GCP-based data lakehouse leveraging BigQuery, GCS, Dataproc, Dataflow, Pub/Sub, Cloud Composer, and BigQuery 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, IoT, remote patient monitoring, and wearables leveraging IoMT patterns.
  • Manage on-prem → cloud migration pipelines, hybrid cloud data movement, VPN/Interconnect connectivity, and data transfer strategies.
  • Build transformation frameworks using BigQuery SQL, Dataflow, Dataproc, or dbt.
  • Define curation patterns including bronze/silver/gold layers, canonical healthcare entities, and data marts.
  • Enable metadata-driven pipelines for scalable transformations.
• Data Governance & Quality
  • Establish and operationalize a data governance framework encompassing data stewardship, ownership, classification, and lifecycle policies.
  • Implement data lineage, data cataloging, and metadata management using tools such as Dataplex, Data Catalog, Collibra, or Informatica.
  • Set up data quality frameworks for validation, profiling, anomaly detection, and SLA monitoring.
  • Ensure HIPAA compliance, PHI protection, IAM/RBAC, VPC SC, DLP, encryption, retention, and auditing.
  • Work with cloud infrastructure teams to architect VPC networks, subnetting, ingress/egress, firewall policies, VPN/IPSec, Interconnect, and hybrid connectivity.
  • Define storage layers, partitioning/clustering design, cost optimization, performance tuning, and capacity planning for BigQuery.
  • Understand containerized processing (Cloud Run, GKE) for data services.
• Stakeholder Collaboration
  • Work closely with clinical, operational, research, and IT stakeholders to define data use cases, schema, and consumption models.
  • Partner with enterprise architects, security teams, and platform engineering teams on cross-functional initiatives.
  • Guide data engineers and provide architectural oversight on pipeline implementation.
  • Be actively hands-on in building pipelines, writing transformations, building POCs, and validating architectural patterns.
  • Mentor data engineers on best practices, coding standards, and cloud-native development.

Required Skills & Qualifications

• Technical Skills (Must-Have)
  • 10+ years in data architecture, engineering, or data platform roles.
  • Strong expertise in GCP data stack (BigQuery, Dataflow, Composer, GCS, Pub/Sub, Dataproc, Dataplex).
  • Hands-on experience with data ingestion, pipeline orchestration, and transformations.
  • Deep understanding of clinical data standards: HL7 v2.x, FHIR, CCD/C-CDA, DICOM (for scans and imaging), LIS/RIS/PACS data structures.
  • Experience with device and IoT data ingestion (wearables, remote patient monitoring, clinical devices).
  • Experience with ERP datasets (Workday, Oracle, Lawson, PeopleSoft).
  • Strong SQL and data modeling skills (3NF, star/snowflake, canonical and logical models).
  • Experience with metadata management, lineage, and governance frameworks.
  • Solid understanding of HIPAA, PHI/PII handling, DLP, IAM, VPC security.
  • Solid understanding of cloud networking, hybrid connectivity, VPC design, firewalling, DNS, service accounts, IAM, and security models.
  • Cloud Native Data movement services.
  • Experience with on-prem to cloud migrations.