CE Data Architect

Organization Overview

Lilly CIA powers the enterprise with governed, AI-ready data products, a converged semantic layer, and the identity and policy infrastructure behind Lilly’s digital experiences. Within CIA, the LillyDirect Covered Entity (CE) Pharmacy pod builds and operates the data platform that sits inside the pharmacy’s covered-entity trust boundary — handling identified PHI under HIPAA with strict isolation from parent-side systems. This role anchors the architecture of that platform.

Position Summary

The CE Data Architect owns the end-to-end data architecture for the CE Pharmacy platform within the covered-entity boundary: the canonical data models, the medallion/lakehouse structure, the identity crosswalk, PHI classification, data contracts, and the isolation controls that keep identified PHI from crossing to parent-side systems without tokenization. This is a governance-first, evidence-based role that translates regulatory and privacy constraints into durable, load-bearing architecture — partnering closely with stewardship, policy-as-code, and engineering to ensure the platform is compliant, auditable, and built to scale.

Key Responsibilities

• Own the canonical CE data architecture — conceptual, logical, and physical models across the Databricks / Unity Catalog medallion (bronze → silver → gold), scoped entirely within the CE trust boundary.
• Model the CE identity and crosswalk layer spanning Reltio MDM, Auth0/Passport, Datavant tokens, Scriptly, Genesys, Prescryptive, and Transcend — defining authoritative-anchor logic and safeguarding merge/split integrity.
• Author and steward data contracts (ODCS) for CE data products, defining schema, quality, freshness/SLA, and lineage expectations between producers and consumers.
• Codify PHI data classification across the ~300-field registry and ensure row/column-level security, masking, and tokenization boundaries are enforced architecturally — not merely documented.
• Design the CE isolation model that prevents identified PHI from crossing to parent-side systems without Datavant tokenization; partner with the Policy-as-Code Engineer to render architectural intent as OPA/Rego.
• Establish reference architecture and patterns so Analytics Engineers and Data Engineers build CE data products consistently and to standard.
• Define lineage, cataloging, and metadata strategy for CE, ensuring end-to-end traceability that supports audit readiness and incident response.
• Provide architectural review and gatekeeping for new CE data flows, integrations, and AI/agent consumption paths.
• Partner across governance and platform — HIPAA governance, Privacy, Legal/DLO, and platform owners (PPH) — to keep the architecture compliant and defensible.
• Enable Skill and agent development — architect the data contracts, reference patterns, and guardrails that let Applied-AI / Agent Engineers build CE Skills and agents against governed data, so PHI classification and consent travel with the data into agentic consumption.
• Supply CI/CD patterns for data, policy, and agent artifacts — define and standardize the pipelines (Azure DevOps, Git-based promotion across dev → test → prod) that version and ship models, ODCS contracts, OPA/Rego policies, Skills, and agents within the CE boundary.

Basic Requirements

• Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field.
• 5+ years of experience in data architecture and/or data engineering, including enterprise-scale delivery.
• SQL and hands-on Databricks / Unity Catalog fluency (notebooks, Delta, catalog/schema/grants).
• Qualified applicants must be authorized to work in the United States on a full-time basis. Lilly will not provide support for or sponsor work authorization or visas for this role, including but not limited to F-1 CPT, F-1 OPT, F-1 STEM OPT, J-1, H-1B, TN, O-1, E-3, H-1B1, or L-1.

Additional Skills / Preferences

• Proficiency with Git-based CI/CD workflows (Azure DevOps or equivalent) for versioned data, contract, and policy artifacts.
• Demonstrated experience designing lakehouse / medallion architectures (Databricks, Unity Catalog, Delta).
• Hands-on data modeling across conceptual, logical, and physical layers, including canonical/converged and dimensional modeling.
• Experience with MDM / identity resolution (Reltio or comparable) and cross-system identifier crosswalks.
• Working knowledge of data governance, classification, and access control (RBAC/ABAC, row- and column-level security).
• Experience in regulated or healthcare data environments; familiarity with HIPAA, PHI handling, and covered-entity constructs.
• Data contract frameworks (ODCS or comparable) and policy-as-code (OPA/Rego) awareness.
• Tokenization / de-identification patterns (Datavant or comparable).
• Pharmacy or patient data flows and consent platforms (Transcend / Cassie).
• Ability to translate architecture clearly for legal, compliance, and engineering audiences.
• Cloud/data architecture certifications (AWS, Databricks).
• Python / PySpark and transformation-as-code (dbt) for reference pipelines, with a test framework (pytest, DLT / Great Expectations).
• Infrastructure-as-code (Terraform) for provisioning Unity Catalog, grants, and the CE isolation boundary.
• Experience architecting or building AI Skills and agents and operationalizing them through CI/CD.