Architecture Programs
Structured, hands-on programs that equip your data engineering team with the skills to design, document, and maintain production-grade data architectures.
DataBlueprintAI programs are not generic training courses. Each program is built around our proprietary blueprint methodology and delivers practical artefacts your team can apply immediately. Participants work on real architecture challenges using our pattern library, design lab tools, and peer review frameworks. Programs are delivered in hybrid format — combining self-paced modules with live design lab sessions at our Toronto campus or via secure video conference.
Feature Store Engineering
A six-week program covering offline and online feature store design. Participants learn to define feature schemas, implement point-in-time correct joins, configure low-latency serving layers, and establish feature governance policies. The program culminates in a blueprint for a production feature store tailored to your organisation's ML workloads.
- Schema design and versioning strategies
- Offline-to-online synchronisation patterns
- Feature monitoring and drift detection
- PIPEDA-compliant data access controls
Pipeline Orchestration
This eight-week program teaches workflow design for batch and streaming data pipelines. Teams learn dependency modelling, retry strategies, dead-letter handling, and observability instrumentation. Graduates produce a complete orchestration blueprint with Airflow, Dagster, or Prefect configurations ready for implementation.
- DAG design and task dependency mapping
- Failure recovery and alerting patterns
- Resource allocation and cost optimisation
- CI/CD integration for pipeline code
ML Blueprint Foundations
Our flagship ten-week program covers the complete blueprint lifecycle from data discovery through model deployment architecture. Ideal for teams building their first ML platform or modernising an existing one. Participants graduate with a full platform blueprint and the skills to maintain it through evolving requirements.
- End-to-end architecture pattern selection
- Data ingestion and storage layer design
- Model training and serving infrastructure
- Governance and compliance integration
Program Delivery Model
Every program follows a consistent structure: foundational modules establish core concepts, applied workshops challenge participants with realistic architecture problems, and a capstone project produces a deliverable blueprint for your organisation. Cohort sizes are limited to twelve participants to ensure meaningful interaction with instructors and peers. All programs include six months of post-graduation blueprint review support.
Programs can be scheduled as open cohorts — joining teams from multiple organisations — or as private engagements for your internal data engineering group. Private programs allow customisation of case studies and pattern selections to match your technology stack and industry requirements.
AI Disclaimer: Program materials may incorporate AI-assisted pattern recommendations and documentation templates. All curriculum content is reviewed and validated by senior data architects. AI tools supplement, not replace, instructor-led design lab sessions and peer review processes.