Data Platform Architect

TailorCare•Montreal, QC

9h•Hybrid

About The Position

TailorCare is a value-based musculoskeletal (MSK) care platform combining clinical expertise, digital tools, and a yield-based operating model. We are now operationalizing Operating Model 3.0, a shift from uniform delivery to yield-based alignment, in which every patient receives investment proportional to a real-time Yield Score (Probability × Value × Addressability), and an ROI Gate continuously calibrates Wallet (financial investment) and Muscle (operational intensity). This requires a data and AI platform that ingests, resolves, scores, decides, and acts in minutes, with the explainability and governance healthcare demands. You will lead that build: set the strategy, design the data platform, drive vendor decisions, and partner with engineering, product, clinical, and operations leadership to deliver it. This is a hybrid strategy-and-architecture role; you will move comfortably from a CTO whiteboard conversation to an EDI 837 parser to a model-evaluation review without losing the thread.

Requirements

10+ years working with healthcare data, including 4+ years in architecture or strategy leadership
Deep hands-on knowledge of healthcare data: X12 EDI (270/271/276/277/278/834/835/837), FHIR R4, HL7 v2 (especially ADT), CCD/C-CDA, NCPDP, and the realities of integrating with payers, EHRs, clearinghouses, and HIEs
Experience working with AI team developing predictive models and ability to act as the liaison between AI modeling and data platform.
Proven track record designing production data platforms at scale, streaming and batch, with managed Kafka or equivalent, lakehouse architectures (Snowflake / Databricks / BigQuery), dbt-style orchestration, modern observability
Solid grounding in ML/AI systems: feature stores, point-in-time correctness, model lifecycle, NLP for clinical text. You evaluate model proposals on their merits
Direct experience with patient identity resolution (deterministic + probabilistic) and tokenization (Datavant or equivalent)
Working knowledge of value-based care economics: MLR, attribution, episode costing, risk adjustment, and how reimbursement models shape data requirements
Demonstrated executive presence: framing tradeoffs, defending recommendations, adjusting when wrong, staying technically credible
HIPAA-fluent. You engineer PHI minimization, BAA structures, and audit requirements as first-class concerns
Ability and willingness to travel up to 10% as needed for onsite meetings, team collaboration, and company events.

Nice To Haves

Hands-on experience with at least one major longitudinal claims dataset (Komodo, Truveta, HealthVerity, Optum, IQVIA) and integration
Highly collaborative and experienced with a broad range of business holders
Experience integrating clinical data networks
Experience with conversational AI in a contact-center context (Cresta, Observe.AI, or built in-house)
Multi-payer scale experience
Early-stage / scaling startup background, comfort with ambiguity and the ability to make calls without perfect information

Responsibilities

Set strategy. Own the multi-year data strategy supporting Operating Model optimization and TailorCare’s extension beyond MSK; frame tradeoffs for the executive team; protect strategic data moats (canonical patient and provider graphs, proprietary outcome labels, and contribute to yield-calibrated decisioning IP)
Architect the platform end-to-end. Ingestion, event bus, identity resolution, lakehouse, feature store, ROI Gate decisioning, action orchestration, observability. Define the event taxonomy, schema registry, and data contracts that govern how every source flows in
Lead vendor strategy. Evaluate and select across clearinghouses, clinical networks, claims systems, provider intelligence, conversational AI, CDPs, and more, negotiating export rights, schema stability, and contribute to defining BAA scope. Build payer-neutral patterns from day one
Set the bar for HIPAA, PHI, and AI governance. Classification at ingestion, field-level access controls, infrastructure-level scrubbing, vendor data governance, training-data lineage, and consent chains.
Partner across functions. Translate architecture into staffed delivery with each engineering team; collaborate with clinical leadership on Patient Reported Outcome, extraction accuracy, and outcome labels; work with operations to make the intake and data aggregation meaningful.
Other duties as assigned