Data Architect – Healthcare Insights, Pharmacy

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

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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, mentor teams, and establish governance standards for data handling.

Highest-signal resume keywords

Expert SQLStrong PythonHands-On Snowflake ExpertiseCloud Data Architecture DesignVector Search and Embeddings

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringData ArchitecturePipeline DesignPerformance TuningSemantic RetrievalHybrid SearchRerankingAdvanced Data ModelingCI/CD StandardsSecurity-By-Design Patterns

Soft Skills

Strong Written CommunicationStrong Verbal CommunicationMentoring

Tools & Technologies

AWSAzureGCPDbtPgvectorPineconeWeaviateOpenSearchElasticSnowflake

Industry Keywords

Data GovernanceRegulated EnvironmentsMature Data Governance ProgramsKnowledge GraphsSemantic Modeling

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformJavaPythonScalaSQL

About the role

Key responsibilities & impact

Own the design and delivery of core AI/context data capabilities
Make end-to-end architecture decisions across unstructured ingestion, embeddings, retrieval, semantic layers, and governance
Design platform architecture from ingestion through 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
Architect and implement semantic layers for BI and agent reasoning
Define data and context contracts for AI inputs
Establish standards for discoverability, documentation, and dataset/index reusability
Own dbt or semantic-layer tooling strategy across workstreams
Own platform 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 retrieval 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 on AI access guardrails
Own governance patterns for sensitive data handling
Drive technical roadmap decomposition with product, AI, and application stakeholders
Facilitate architectural decisions and alignment across teams without direct authority
Mentor engineers through design reviews, code reviews, and documentation
Potentially lead a small engineering team in the future, 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
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
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
Comfortable with the trajectory toward direct people leadership

Benefits

Comp & perks

Annual incentive compensation program
Medical coverage
Dental coverage
Vision coverage
Wellness programs