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Huron

Data Architect – Healthcare Insights, Revenue Cycle

Huron

. Own the design and delivery of core AI/context data capabilities .

Posted 9/29/2026full-timeRemote • Illinois • United StatesSeniorLead💰 $140,000 - $190,000 per yearWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in data engineering and architecture, with a strong focus on AI capabilities, cloud data solutions, and performance optimization. Proven ability to lead cross-functional initiatives, establish engineering standards, and mentor teams in a production environment.

Highest-signal resume keywords
Expert SQLStrong PythonHands-On Snowflake ExpertiseCloud Data Architecture on AWS, Azure, or GCPVector Search and Embeddings

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
Data EngineeringData ArchitecturePipeline DesignPerformance TuningSemantic RetrievalHybrid SearchRerankingData ModelingCI/CDSecurity-By-Design Patterns
Soft Skills
Strong Written CommunicationStrong Verbal CommunicationCross-Functional LeadershipMentoring
Tools & Technologies
SnowflakeDbtAWSAzureGCPPgvectorPineconeWeaviateOpenSearchElastic
Industry Keywords
Data GovernanceRegulated EnvironmentsKnowledge GraphsSemantic ModelingLakehouse

Tech Stack

Tools & technologies
AWSAzureCloudGoogle Cloud PlatformJavaPythonScalaSQL

About the role

Key responsibilities & impact
  • Own the design and delivery of core AI/context data capabilities
  • Design end-to-end platform architecture covering ingestion, parsing/chunking, enrichment, embeddings, vector indexing, and retrieval/serving
  • Define scalable patterns for incremental refresh, backfills, re-embeddings, deduplication, and lineage across unstructured sources
  • Set technical direction for retrieval quality, including query strategies, hybrid search, metadata filtering, and reranking
  • Evaluate and select infrastructure, tooling, and cloud services across AWS, Azure, and GCP environments
  • Architect and implement semantic layers for BI and agent reasoning
  • Define data contracts and context contracts for AI inputs
  • Establish standards for discoverability, documentation, and reusability across datasets and indexes
  • Own the dbt or semantic layer tooling strategy
  • Own platform-level reliability and performance, including 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
  • Implement security-by-design patterns, including RBAC/ABAC, PII redaction, retention controls, audit logging, and safe agent-tool access
  • Partner with Security, Legal, and Compliance to define and enforce AI access guardrails
  • Own governance patterns for sensitive data handling
  • Drive technical roadmap decomposition with product, AI, and application stakeholders
  • Facilitate architectural decisions and build alignment across teams without direct authority
  • Set best practices and mentor engineers through design reviews, code reviews, and documentation
  • Grow into formal people leadership, including hiring input, technical development, and delivery oversight

Requirements

What you’ll need
  • 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
  • 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, including pgvector, Pinecone, Weaviate, OpenSearch, or Elastic
  • Experience with retrieval patterns, including semantic retrieval, hybrid search, and reranking
  • Experience with dbt or comparable semantic layer tooling in a production environment
  • Ability to lead cross-functional technical initiatives and drive alignment across teams
  • Strong written and verbal communication skills for technical and non-technical audiences
  • Candidates should be comfortable with the trajectory toward direct people leadership and motivated to build and shape a team
  • Preferred: Experience supporting LLM applications, including RAG, agent tool interfaces, and evaluation/observability
  • Preferred: Knowledge of knowledge graphs, semantic modeling, or metrics layers at scale
  • Preferred: Experience in regulated environments and mature data governance programs
  • Preferred: Familiarity with Iceberg, Delta Lake, or other open table formats in a lakehouse context
  • Preferred: Prior formal or informal technical lead or staff engineer experience

Benefits

Comp & perks
  • Annual incentive compensation program
  • Medical coverage
  • Dental coverage
  • Vision coverage
  • Wellness programs
  • Huron benefit plans