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About the Role
As Data Architect for MediCore, you will own the platform's data strategy and architecture, covering data ingestion, modeling, security, governance, and availability for analytics and AI. You will collaborate with engineering, product, AI/ML, and implementation teams to design a scalable data foundation that meets strict healthcare privacy requirements.
Responsibilities
- Define and own MediCore's end-to-end data architecture, including operational databases, data warehouse, streaming pipelines, and data services.
- Design scalable data models for patient access, scheduling, referrals, and clinic operations data.
- Architect ingestion and integration pipelines for EHR/EMR and practice management data using HL7 v2, FHIR, and third-party APIs.
- Build and govern the analytics platform on Google Cloud using BigQuery, Dataflow, Pub/Sub, Cloud Composer, and Cloud Storage.
- Design data foundations for AI/ML and LLM features, including feature pipelines, embeddings and vector storage, and training and evaluation datasets.
- Establish data governance, including data quality, lineage, cataloging, master data management, and retention policies.
- Design multi-tenant data isolation and residency strategies for customers in Canada, US, Mexico, and Latin America.
- Ensure data handling meets healthcare privacy and security standards (HIPAA, PHIPA, SOC 2).
- Define reporting and analytics capabilities for customers.
- Set data engineering standards, review designs, and mentor engineers on data modeling and pipeline best practices.
- Work with implementation teams to plan data migrations and integrations for new health system and clinic customers.
Requirements
- 10+ years of experience in data engineering, data architecture, or related roles.
- At least 3 to 4 years in an architect or technical lead role.
- Deep expertise in data modeling (relational, dimensional, and event-driven) and designing both OLTP and analytical systems.
- Strong hands-on experience with Google Cloud data services, including BigQuery, Dataflow, Pub/Sub, Cloud SQL, Cloud Storage, and Cloud Composer (Airflow).
- Expert SQL and strong Python skills for data pipelines and tooling.
- Experience designing batch and real-time streaming pipelines at scale.
- Solid experience with PostgreSQL, including performance tuning, partitioning, and replication.
- Experience implementing data governance, data quality frameworks, and metadata management.
- Strong understanding of data security, privacy, and access control in regulated environments.
- Excellent communication skills and the ability to explain architectural decisions to technical and non-technical stakeholders.
- Spanish proficiency.
Skills
- Data Architecture
- Data Engineering
- Data Modeling
- Google Cloud Platform
- BigQuery
- Dataflow
- Pub/Sub
- Cloud SQL
- Cloud Storage
- Cloud Composer
- Airflow
- SQL
- Python
- Streaming Pipelines
- PostgreSQL
- Data Governance
- Data Quality
- Metadata Management
- Data Security
- Data Privacy
- Access Control
- HL7
- FHIR
- EHR Data
- Google Cloud Healthcare API
- HIPAA
- PHIPA
- De-identification
- AI/ML
- Vertex AI
- Feature Stores
- Vector Databases
- RAG Pipelines
- dbt
- Dataplex
- Looker
- SaaS Data Architectures
- Google Cloud Professional Data Engineer
- Google Cloud Professional Cloud Architect
Location
- Toronto
- Canada
- US
- Mexico
- Latin America
Work Type
- Full-time
Experience Level
- 10+ years of experience
- 3-4 years in an architect or technical lead role
Benefits
- Competitive compensation
- Benefits
- Professional development support, including certifications
About the Company
- Rules Cube is a Toronto-based digital transformation and Pega consulting firm with offices in Canada, US, Mexico, and Latin America.
- MediCore is Rules Cube's AI-powered patient access and clinic operations platform that helps health systems, clinics, and diagnostic networks streamline scheduling, intake, referrals, and front-office operations.
- MediCore is growing across North and Latin America.