Data Architect – Healthcare Insights, Revenue Cycle

This is a fully remote position, open to applicants in Illinois.

📋 Description

• Take ownership of the design and execution of essential AI/context data capabilities.

• Create a comprehensive platform architecture that includes ingestion, parsing/chunking, enrichment, embeddings, vector indexing, and retrieval/serving.

• Establish scalable methodologies for incremental refreshes, backfills, re-embeddings, deduplication, and data lineage across unstructured sources.

• Determine technical direction for retrieval quality, focusing on query strategies, hybrid search, metadata filtering, and reranking.

• Assess and choose infrastructure, tools, and cloud services across AWS, Azure, and GCP environments.

• Design and implement semantic layers for business intelligence and agent reasoning.

• Specify data contracts and context agreements for AI inputs.

• Set standards for discoverability, documentation, and reusability for datasets and indexes.

• Manage the dbt or semantic layer tooling strategy.

• Oversee platform-level reliability and performance, including monitoring, alerting, SLAs/SLOs, runbooks, incident response, and postmortems.

• Optimize costs and latency across Snowflake, lakehouse, and vector infrastructure.

• Establish engineering standards for continuous integration/continuous deployment (CI/CD), testing, and evaluation.

• Apply security-by-design principles, including RBAC/ABAC, PII redaction, retention controls, audit logging, and secure agent-tool access.

• Collaborate with Security, Legal, and Compliance to define and enforce AI access guardrails.

• Manage governance protocols for handling sensitive data.

• Drive the breakdown of technical roadmaps in collaboration with product, AI, and application stakeholders.

• Facilitate architectural decisions and build consensus among teams without direct authority.

• Establish best practices and mentor engineers through design reviews, code reviews, and documentation.

• Evolve into formal people leadership responsibilities, including input on hiring, technical development, and oversight of delivery.

⛳️ Requirements

• 8–12+ years of experience in data engineering, data architecture, or platform roles with substantial hands-on delivery.

• Proficient in SQL and strong in Python (or Scala/Java).

• Possess deep production engineering habits.

• Demonstrated hands-on expertise with Snowflake, covering advanced data modeling, pipeline design, performance tuning, and large-scale production operations.

• Experience in designing cloud data architectures on AWS, Azure, or GCP, encompassing storage, compute, orchestration, and networking considerations.

• Practical experience with vector search and embeddings, including pgvector, Pinecone, Weaviate, OpenSearch, or Elastic.

• Familiarity with retrieval methodologies, such as semantic retrieval, hybrid search, and reranking.

• Experience using dbt or similar semantic layer tools in a production setting.

• Capability to lead cross-functional technical initiatives and foster alignment across teams.

• Strong written and verbal communication skills for both technical and non-technical audiences.

• Candidates should be open to transitioning into direct people leadership roles and be motivated to build and develop a team.

• Preferred: Experience in 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 established data governance programs.

• Preferred: Familiarity with Iceberg, Delta Lake, or other open table formats in a lakehouse context.

• Preferred: Prior formal or informal experience as a technical lead or staff engineer.

🏝️ Benefits

• Annual performance-based incentive compensation program.

• Medical insurance coverage.

• Dental insurance coverage.

• Vision insurance coverage.

• Wellness programs.

• Huron benefit plans.