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# Data Architect - Healthcare Insights - Supply...

- **Company:** Huron Consulting Group Inc.
- **Location:** Chicago, IL, United States (Remote available)
- **Experience:** Expert
- **Salary:** $140,000.0 - $190,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Audit Trail, Microsoft Azure, Cloud Database, Code Review, Continuous Integration, Data Architecture, Data Deduplication, Information Engineering, Data Governance, Software Design Patterns, Graph Database, Python (Programming Language), Performance Tuning, Role-Based Access Control, Regression Testing, Power BI, Cloud Services, Search Technologies, SQL Databases, Data Processing, Large Language Models, Snowflake, Mttr, Data Layers, Data Lakes, Information Technology
- **Published:** July 13, 2026
- **Apply:** https://www.juju.com/job/00000000gfz3em

## About the Role

+ Ability to travel as needed up to 4 times per year., + Bachelor's Degree in computer science, engineering, or related field of study

 + 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 Snowflakeexpertiseincluding advanced data modeling, pipeline design, performance tuning, andoperatingat 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 withdbtor 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

Preferred Qualifications

 + Experience supporting LLM applications (RAG, agent tool interfaces, evaluation/observability)

 + Knowledge of knowledge graphs, semantic modeling, or metrics layers at scale

 + Experience in regulated environments and mature data governance programs

 + Familiarity with Iceberg, Delta Lake, or other open table formats in alakehousecontext

 + Prior experience in a formal or informal technical lead or staff engineer capacity

Example Success Measures

 + Measurable improvement in AI outcomes: higher retrieval precision/recall, better citation coverage, fewer "missing context" failures

 + Reduced latency/cost per retrieval and improved platform reliability (SLO attainment, lower MTTR)

 + Broad adoption of semantic definitions, context contracts, and platform standards across teams

 + Architecture decisions are well-documented, defensible, and enable downstream engineers to deliver faster

## Description

_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 thedbtor semantic layer tooling strategy and ensure consistent application across workstreams

_Operational excellence_

 + 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)

_A_ _I safety, governance, and compliance_

 + 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

_Lead through influence_

 + 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

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., + **Business-curious and domain-eager:** Proactively learns healthcare processes, terminology, and KPIs - can speak credibly with SMEs and business leaders, not just translate requirements but help shape the right questions and success measures

 + **Stakeholder-first collaborator:** Builds strong relationships with stakeholders, SMEs, and consultants; clarifies goals, constraints, and tradeoffs early; communicates progress and risks clearly; sets realistic expectations around timelines, scope, and quality

 + **Consultative problem-solver:** Approaches requests with a "diagnose before prescribe" mindset - asks smart questions, proposes options, and guides teams toward durable solutions rather than one-off fixes

 + **Influence without authority:** Leads throughexpertiseand trust - drives alignment,facilitatesdecisions, and unblocks teams across functions without relying on positional authority

 + **High ownership and follow-through:** Treats reliability, documentation, and operational readiness as part of the work; finishes what they start; holds a high bar for production quality

 + **Clear communicator for mixed audiences:** Can go deep with engineers and explain concepts plainly to non-technical partners; writes crisp architecture docs, designs, and runbooks

 + **Pragmatic builder mindset:** Biases toward shipping value in iterations,validatingwith users, and improving based on feedback - balancing innovation with maintainability and risk

 + **Comfortable with ambiguity:** Thrives in early-stage or evolving spaces, adapts quickly, and turns unclear goals into actionable architectural plans

 + **Integrity and stewardship:** Handles sensitive data responsibly, advocates for secure-by-design patterns, and enables the business to move fast without cutting corners on governance


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