Lead Data Informaticist

The Lead Informaticist serves as a senior technical individual contributor responsible for building and governing the data and analytical foundation supporting Center Well Traditional Pharmacy's evolving analytics environment.

This role will design and develop curated data products, scalable ETL/ELT pipelines, metadata, business definitions, and analytical standards that enable analysts and business partners to reliably use Databricks Genie One and other AI‑assisted analytical capabilities. The Lead Informaticist is responsible not only for making data available, but for ensuring that the analytical environment understands how the business expects that data to be used, including appropriate KPI calculations, relationships between data sources, populations, business rules, and analytical definitions.

You will also monitor how AI‑assisted analytical environments answer business questions, identify gaps in existing governed data capabilities, and develop solutions that bridge those gaps. This may include integrating traditionally different information such as pharmacy claims, membership, marketing, operational, and financial data to allow end‑to‑end evaluation of performance and financial impact.

Internal CeDAR planning materials similarly emphasize governed assumptions, reproducible analytical infrastructure, and increasing the share of partner questions that can be answered without a traditional modeling request. This role is intended to directly enable that type of model.

The Lead Informaticist is a senior technical individual contributor who provides hands‑on technical leadership for the data products, analytical architecture, metadata, business rules, and governance supporting Center Well Traditional Pharmacy analytics.

• Design, develop, test, deploy, document, and maintain scalable ETL/ELT pipelines and curated analytical data products within Databricks.
• Translate analytical and business requirements into reusable data models that appropriately represent pharmacy claims, membership, operational, marketing, financial, and other business domains.
• Define and maintain documentation and metadata describing data sources, table and field definitions, analytical grain, relationships, lineage, refresh expectations, transformation logic, and intended usage.
• Encode and govern business logic supporting key performance indicators, business definitions, population rules, source relationships, and approved analytical methodologies.
• Establish appropriate methods for joining and integrating disparate data sources while protecting the integrity and intended meaning of each source.
• Build curated data environments designed to support reliable AI‑assisted and self‑service analytics through tools such as Databricks Genie One.
• Evaluate the accuracy, completeness, consistency, and repeatability of answers generated through AI‑assisted analytical environments.
• Identify patterns of business questions that cannot be reliably answered using currently governed information and determine whether the appropriate solution is new data, new business logic, enhanced metadata, additional integration, or another analytical capability.
• Develop data and analytical bridges across traditionally separate domains when required to answer complex business questions, including connections among pharmacy claims, membership, marketing activity, operational throughput, and financial outcomes.
• Establish automated and repeatable data‑quality controls, reconciliations, validation processes, and monitoring to support trustworthy analytical outputs.
• Partner closely with business‑facing informaticists and analysts to understand emerging business questions and convert recurring…