At a Glance
- Tasks: Own the data strategy for an AI-powered healthcare platform and design scalable data architectures.
- Company: Join a Toronto-based digital transformation firm with a global presence.
- Benefits: Competitive pay, benefits, and support for professional development and certifications.
- Other info: Collaborative international team with opportunities for growth and influence.
- Why this job: Shape the future of healthcare data and AI across multiple countries.
- Qualifications: 10+ years in data architecture, strong Google Cloud and SQL skills, and excellent communication.
The predicted salary is between 123750 - 151250 $ per year.
About Rules Cube and MediCore
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.
The Role
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.
What You'll Do
- 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.
What You Bring
- 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.
Nice to Have
- 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.
Why Join Us
- 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.
Data Architect in Toronto employer: Rules Cube
At Rules Cube, we pride ourselves on being an exceptional employer, offering a dynamic work environment that fosters innovation and collaboration. As a Data Architect for MediCore, you'll not only shape the data strategy of a cutting-edge healthcare AI platform but also enjoy competitive compensation, comprehensive benefits, and ample opportunities for professional growth within our diverse, international team. Join us in Toronto and be part of a mission-driven company that values your expertise and empowers you to make a meaningful impact in the healthcare sector.
