Data Architect - Healthcare Insights - Supply Chain (Manager)

Role Description

This role sits within a strategic investment to embed AI into how we operate, serve customers, and make decisions within our healthcare business. We're building a healthcare-wide AI data and context platform with a focus on deep domain expertise embedded throughout our architecture. Our goals are:

• Turn structured and unstructured information into trusted, reusable "building blocks" (semantic layers, retrieval services, and agent-ready interfaces) that accelerate product innovation.
• Deliver transformational speed and leverage — faster time-to-insight, higher automation of knowledge work, and a foundation that scales AI safely and reliably as adoption grows.
• Unlock new capabilities across our business and create the foundation that drives deeper domain innovation and cross-domain collaboration.

This is a hands-on technical architect who owns the design and delivery of core AI/context data capabilities. The role is responsible for end-to-end architecture decisions across the platform — unstructured ingestion, embeddings, retrieval, semantic layers, and governance — while partnering across engineering, product, and AI teams to ship production-grade AI data products. Leadership is through technical ownership, design authority, and cross-functional influence.

Qualifications

• 8–12+ years in data engineering, data architecture, or platform roles with significant hands-on delivery.
• Expert SQL and strong Python (or Scala/Java); deep production engineering habits.
• Hands-on Snowflake expertise including advanced data modeling, pipeline design, performance tuning, and operating at scale in production.
• Proven experience designing cloud data architectures on AWS, Azure, or GCP — including storage, compute, orchestration, and networking considerations.
• Hands-on experience with vector search and embeddings (pgvector/Pinecone/Weaviate/OpenSearch/Elastic) and retrieval patterns (semantic retrieval, hybrid search, reranking).
• Experience with dbt or comparable semantic layer tooling in a production environment.
• Demonstrated ability to lead cross-functional technical initiatives and drive alignment across teams.
• Strong written and verbal communication skills — able to present architecture decisions to both technical and non-technical audiences.

Requirements

• Architect and own the AI context platform.
• Design end-to-end platform architecture: ingestion → parsing/chunking → enrichment → embeddings → vector indexing → retrieval/serving.
• Define scalable patterns for incremental refresh, backfills, re-embeddings, deduplication, and lineage across unstructured sources.
• Set technical direction for retrieval quality (query strategies, hybrid search, metadata filtering, reranking) in partnership with AI engineers.
• Evaluate and select infrastructure, tooling, and cloud services to support platform needs across AWS/Azure/GCP environments.
• Design and deliver semantic and governed data products.
• Architect and implement semantic layers (metrics/entities) that power BI and agent reasoning consistently across the platform.
• Define data contracts and context contracts for AI inputs (schemas, metadata requirements, freshness, citation expectations).
• Establish standards for discoverability, documentation, and reusability across datasets and indexes.
• Own the dbt or semantic layer tooling strategy and ensure consistent application across workstreams.
• Own reliability and performance at the platform level: monitoring, alerting, SLAs/SLOs, runbooks, incident response, and postmortems.
• Drive cost and latency optimization across Snowflake, lakehouse, and vector infrastructure.
• Set engineering standards for CI/CD, testing, and evaluation (retrieval eval sets, regression tests, online telemetry).
• Implement security-by-design: RBAC/ABAC patterns, PII redaction, retention controls, audit logging, and safe access pathways for agent tools.
• Partner with Security/Legal/Compliance to define and enforce guardrails for AI access to enterprise knowledge.
• Own governance patterns for sensitive data handling across the platform.
• Drive technical roadmap decomposition with product, AI, and application stakeholders.
• Facilitate architectural decisions across teams and functions, building alignment without direct authority.
• Set best practices and mentor engineers via design reviews, code reviews, and documentation.

Benefits

• Estimated base salary: $140,000 - $190,000 USD.
• Total estimated compensation range (including annual incentive compensation): $161,000 - $237,500 USD.
• Eligible to participate in Huron’s benefit plans which include medical, dental, and vision coverage and other wellness programs.

Future Scope

This role is expected to grow into direct people leadership over time. As the platform matures and the engineering team expands, the Architect will take on formal responsibility for leading a small team of engineers — owning hiring input, technical development, and delivery oversight. Candidates should be comfortable with that trajectory and motivated by the opportunity to build and shape a team from an early stage.

Travel Expectations

• Ability to travel as needed up to 4 times per year.

Behavioral Attributes

• Business-curious and domain-eager: Proactively learns healthcare processes, terminology, and KPIs.
• Stakeholder-first collaborator: Builds strong relationships with stakeholders, SMEs, and consultants.
• Consultative problem-solver: Approaches requests with a "diagnose before prescribe" mindset.
• Influence without authority: Leads through expertise and trust.
• High ownership and follow-through: Treats reliability, documentation, and operational readiness as part of the work.
• Clear communicator for mixed audiences: Can go deep with engineers and explain concepts plainly to non-technical partners.
• Pragmatic builder mindset: Biases toward shipping value in iterations, validating with users, and improving based on feedback.
• Comfortable with ambiguity: Thrives in early-stage or evolving spaces.
• Integrity and stewardship: Handles sensitive data responsibly and advocates for secure-by-design patterns.