Lead Data Informaticist

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• The Lead Informaticist serves as a senior technical individual contributor responsible for building and governing the data and analytical foundation supporting CenterWell 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 CenterWell Traditional Pharmacy analytics.

Key responsibilities include:

• •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 analytical needs into scalable capabilities.
• •Ensure that important business definitions and analytical rules are implemented consistently rather than repeatedly recreated within individual analyses.
• •Provide technical leadership through architecture recommendations, design standards, peer review, documentation standards, mentoring, and identification of reusable development patterns.
• •Support source-to-target documentation, change management, version control, testing, and deployment practices for critical analytical assets.
• •Partner with data engineering, technology, finance, marketing, pharmacy, and other cross-functional teams when solutions require integration beyond the existing analytical environment.
• •Continuously evaluate emerging data and AI capabilities and determine how they can responsibly improve analytical scalability, accessibility, governance, and business decision support.

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Required Qualifications

• •Bachelor's degree in computer science, data engineering, analytics, informatics, information systems, mathematics, statistics, or another quantitative or technology-related field, or equivalent relevant professional experience.
• •Seven or more years of experience in data analytics, informatics, business intelligence, data engineering, analytical engineering, or a related discipline (including graduate and post graduate experience).
• •Demonstrated experience leading complex analytical-data, data-product, or analytical-platform initiatives.
• •Hands-on experience working in modern cloud-based data and analytics environments.
• •Strong SQL proficiency and demonstrated experience developing complex analytical transformations and reusable data assets.
• •Demonstrated experience designing, developing, testing, and maintaining ETL/ELT pipelines.
• •Experience with dimensional, relational, or analytical data modeling and designing data structures for downstream analytics and reporting.
• •Experience with data quality, reconciliation, testing, metadata, lineage, documentation, and analytical governance practices.
• •Experience working with healthcare, payer, claims, pharmacy, or other complex healthcare datasets.
• •Strong understanding of data grain, source relationships, business rules, aggregations, populations, and the implications of combining disparate data sources.
• •Ability to translate business definitions and analytical methodologies into scalable, repeatable technical solutions.
• •Demonstrated ability to troubleshoot complex data problems and determine root causes across upstream and downstream processes.
• •Strong written and verbal communication skills with the ability to explain technical architecture, data limitations, and analytical implications to both technical and non-technical audiences.
• •Demonstrated ability to provide technical leadership, influence standards, and guide analytical solutions across teams.

Preferred Qualifications

• •Master's degree in computer science, data engineering, analytics, informatics, information systems, data science, statistics, or another related discipline.
• •Significant hands-on experience with Databricks and its associated data and analytics ecosystem.
• •Experience developing curated data products specifically for AI-assisted analytics, natural-language analytics, or governed self-service analytical environments.
• •Experience configuring or supporting Databricks Genie One or similar AI-assisted analytical capabilities.
• •Experience with Python or another programming language used for data engineering, automation, testing, or advanced analytics.
• •Direct experience with pharmacy or prescription claims data, including knowledge of common pharmacy business concepts and healthcare data structures.
• •Experience within payer, PBM, mail-order pharmacy, Medicare, or related healthcare environments.
• •Experience integrating pharmacy claims, membership, marketing, operational, and financial information for cross-functional analysis.
• •Experience developing or governing enterprise KPI definitions, semantic layers, reusable measures, metadata, or business-rule frameworks.
• •Experience with enterprise data catalogs, data lineage, data governance, access controls