Data Architect – Healthcare Insights, Pharmacy

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

📋 Description

• Take charge of the design and implementation of fundamental AI/context data functionalities.

• Make comprehensive architectural decisions regarding unstructured data ingestion, embeddings, retrieval, semantic layers, and governance.

• Develop platform architecture from data ingestion to parsing/chunking, enrichment, embeddings, vector indexing, and retrieval/serving.

• Establish scalable methods for incremental updates, backfills, re-embeddings, deduplication, and lineage across unstructured sources.

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

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

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

• Define data and context agreements for AI inputs.

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

• Oversee the strategy for dbt or semantic-layer tools across various workstreams.

• Ensure platform 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 CI/CD, testing, and retrieval evaluation.

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

• Collaborate with Security, Legal, and Compliance teams on AI access guardrails.

• Manage governance strategies for sensitive data handling.

• Lead the decomposition of the technical roadmap in collaboration with product, AI, and application stakeholders.

• Facilitate architectural decision-making and alignment across teams without direct authority.

• Mentor engineers through design reviews, code reviews, and documentation processes.

• Potentially lead a small engineering team in the future, including contributions to hiring, technical development, and delivery oversight.

⛳️ 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 skills.

• Hands-on experience with Snowflake, including advanced data modeling, pipeline design, performance optimization, and operating at scale in production environments.

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

• Practical knowledge of vector search and embeddings, including pgvector, Pinecone, Weaviate, OpenSearch, or Elastic.

• Familiarity with retrieval methods including semantic retrieval, hybrid search, and reranking.

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

• Ability to lead cross-functional technical projects and foster alignment across teams.

• Excellent written and verbal communication skills.

• Preferred: experience supporting LLM applications, including RAG, agent tool interfaces, and evaluation/observability.

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

• Comfortable with the path toward direct people leadership.

🏝️ Benefits

• Annual incentive compensation program.

• Medical coverage.

• Dental coverage.

• Vision coverage.

• Wellness programs.