[Hiring] Lead Data Informaticist @Humana

Role Description

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 for:

• Making data available and ensuring the analytical environment understands how the business expects that data to be used.
• Monitoring how AI-assisted analytical environments answer business questions and identifying gaps in existing governed data capabilities.
• Integrating traditionally different information such as pharmacy claims, membership, marketing, operational, and financial data.
• Providing hands-on technical leadership for data products, analytical architecture, metadata, business rules, and governance.

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.
• Develop data and analytical bridges across traditionally separate domains when required to answer complex business questions.
• Establish automated and repeatable data-quality controls, reconciliations, validation processes, and monitoring.
• Partner closely with business-facing informaticists and analysts to understand emerging business questions.
• Ensure that important business definitions and analytical rules are implemented consistently.
• 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 cross-functional teams when solutions require integration beyond the existing analytical environment.
• Continuously evaluate emerging data and AI capabilities to improve analytical scalability, accessibility, governance, and business decision support.

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.
• 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.
• 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.
• Strong written and verbal communication skills.
• Demonstrated ability to provide technical leadership, influence standards, and guide analytical solutions across teams.

Requirements

• Master's degree in computer science, data engineering, analytics, informatics, information systems, data science, statistics, or another related discipline (preferred).
• Significant hands-on experience with Databricks and its associated data and analytics ecosystem (preferred).
• Experience developing curated data products specifically for AI-assisted analytics (preferred).
• Experience configuring or supporting Databricks Genie One or similar AI-assisted analytical capabilities (preferred).
• Experience with Python or another programming language used for data engineering (preferred).
• Direct experience with pharmacy or prescription claims data (preferred).
• Experience within payer, PBM, mail-order pharmacy, Medicare, or related healthcare environments (preferred).
• Experience integrating pharmacy claims, membership, marketing, operational, and financial information for cross-functional analysis (preferred).
• Experience developing or governing enterprise KPI definitions, semantic layers, reusable measures, metadata, or business-rule frameworks (preferred).
• Experience with enterprise data catalogs, data lineage, data governance, access controls, and healthcare data privacy requirements (preferred).
• Experience implementing version control, code review, testing, deployment, and other data-development lifecycle practices (preferred).
• Experience designing analytical assets that serve multiple audiences (preferred).

Benefits

• Medical, dental and vision benefits.
• 401(k) retirement savings plan.
• Time off (including paid time off, company and personal holidays, paid parental and caregiver leave).
• Short-term and long-term disability.
• Life insurance.
• Many other opportunities for personal wellness and smart healthcare decisions.

Scheduled Weekly Hours

40

Pay Range

The compensation range below reflects a good faith estimate of starting base pay for full time (40 hours per week) employment at the time of posting. The pay range may be higher or lower based on geographic location and individual pay will vary based on demonstrated job related skills, knowledge, experience, education, certifications, etc.

$117,600 - $161,700 per year. This job is eligible for a bonus incentive plan based on company and/or individual performance.