Data Architect

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. It helps health systems, clinics, and diagnostic networks streamline scheduling, intake, referrals, and front-office operations so patients get care faster and staff spend less time on manual work. MediCore is growing across North and Latin America, and we're building out the team behind it.

As Data Architect for MediCore, you'll own the platform's data strategy and architecture, covering how clinical and operational data is ingested, modeled, secured, governed, and made available for analytics and AI. You'll work closely with engineering, product, AI/ML, and implementation teams to design a data foundation that scales across customers and countries while meeting strict healthcare privacy requirements.

• 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, balancing transactional performance with analytics needs.
• 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), including encryption, de-identification, access controls, and audit logging.
• Define reporting and analytics capabilities for customers, such as operational dashboards, KPIs, and data exports.
• 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.

• 10+ years of experience in data engineering, data architecture, or related roles, including 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.

• Healthcare data experience, especially with HL7, FHIR, EHR data, or the Google Cloud Healthcare API.
• Familiarity with HIPAA, PHIPA, or other healthcare compliance frameworks, including de-identification techniques.
• Experience building data platforms for AI/ML, including Vertex AI, feature stores, vector databases, or RAG pipelines.
• Experience with dbt, Dataplex, Looker, or similar modeling, governance, and BI tools.
• Experience designing multi-tenant SaaS data architectures.
• Google Cloud Professional Data Engineer or Professional Cloud Architect certification.
• Spanish proficiency, to support MediCore's growing customer base in Mexico and Latin America.

• Shape the data foundation of a healthcare AI platform used across multiple countries.
• Work at the intersection of healthcare data, analytics, and AI with real ownership and influence.
• The pace of a product team with the stability of an established firm.
• Collaborative, international team spanning Canada, the US, and Latin America.
• Competitive compensation, benefits, and professional development support, including certifications.