AI and Data - Data Architect - Healthcare
- Toronto, ON
- Permanent
- Full-time
- Lead enterprise-level architecture for Health data platforms across ingestion, streaming, transformation, storage, APIs, and analytics consumption
- Act as a senior technical authority, mentoring engineers and shaping architectural direction across stakeholders and teams
- Lead cross-functional projects involving healthcare IT professionals, data scientists, and clinical stakeholders
- Integrate agentic AI systems into data platforms to enable autonomous monitoring, orchestration, optimization, and remediation of data workflows
- Leverage AI agents to support metadata enrichment, lineage intelligence, data quality automation, and real-time anomaly detection
- Adopt AI-assisted engineering practices to accelerate design, prototyping, and architectural validation
- Define patterns for safe, compliant, and governed usage of agentic AI across the data ecosystem
- Architect and oversee complex data workflows and high-volume streaming pipelines, leveraging platforms such as Kafka, Pub/Sub, Apache Flink, Dataflow, PySpark
- Define architectural patterns for event-driven, stateful, and hybrid batch/stream systems
- Establish standards for data modeling, schema governance, versioning, and interoperability including FHIR R4+
- Embed data governance, privacy, compliance, and reliability into platform design
- Design data-centric microservices and APIs with strong data contracts and lifecycle management
- Degree in computer science, computer engineering or related discipline
- 10+ years designing and delivering large-scale data platforms
- Deep expertise in data architecture, including streaming pipelines, complex transformations, and distributed data processing
- Proven ability to design end-to-end systems integrating data pipelines, storage, APIs, and services
- Strong understanding of event-driven architectures and data-centric microservices
- Experience with Hospital Information Systems (HIS) data and data ecosystems
- Experience with clinical data models and data exchange standards (e.g., HL7 FHIR v2, CDA, IHE, etc.)
- Hands-on experience with cloud-native data platforms, including services such as Pub/Sub, Dataflow, BigQuery, Kafka, Flink, PySpark-preferably on Azure
- Familiarity with modern development practices and experience with AI-assisted coding and productivity tools
- Strong understanding of data governance, security, and privacy in regulated environments
- Experience or interest in leveraging agentic AI to automate engineering workflows, enhance observability, and improve platform reliability
- Understanding of safe and compliant use of autonomous AI agents in regulated healthcare environments
- Support and coaching from some of the most engaging colleagues in the industry
- Learning opportunities to develop new skills and progress your career
- The freedom and flexibility to handle your role in a way that's right for you