Lead Data Informaticist

<h3>Accountabilities</h3><li>Design, develop, test, deploy, document, and maintain scalable ETL/ELT pipelines and curated analytical data products within Databricks and other modern data environments.</li><li>Translate business and analytical requirements into reusable data models that accurately represent pharmacy claims, membership, marketing, operational, financial, and other business domains.</li><li>Develop and maintain comprehensive metadata and documentation covering data sources, table and field definitions, analytical grain, relationships, lineage, refresh schedules, transformation logic, and intended usage.</li><li>Define, implement, and govern business rules, KPI calculations, population criteria, source relationships, and approved analytical methodologies to ensure consistent interpretation across teams.</li><li>Establish reliable methods for joining and integrating disparate datasets while preserving source integrity, business context, and analytical accuracy.</li><li>Build curated data environments that support governed self-service analytics and AI-assisted analytical tools, including Databricks Genie One.</li><li>Evaluate the accuracy, completeness, consistency, and reproducibility of AI-generated analytical responses, identifying gaps in existing data structures, business definitions, and governed capabilities.</li><li>Investigate recurring business questions that cannot be answered reliably using existing data assets and determine whether solutions require additional datasets, improved metadata, new business logic, or enhanced integrations.</li><li>Develop analytical connections across traditionally separate domains, enabling end-to-end analysis of pharmacy claims, membership, marketing activities, operational performance, and financial outcomes.</li><li>Implement automated data-quality controls, reconciliation processes, validation frameworks, and monitoring mechanisms to ensure trustworthy analytical outputs.</li><li>Partner with business-facing informaticists and analysts to understand emerging requirements and convert recurring analytical needs into scalable, reusable data capabilities.</li><li>Standardize important business definitions and analytical methodologies to minimize duplicated work and ensure consistency across reports, dashboards, and analytical applications.</li><li>Provide technical leadership through architecture recommendations, design standards, peer reviews, documentation practices, mentoring, and reusable development patterns.</li><li>Maintain source-to-target documentation and support change management, version control, testing, and deployment practices throughout the data development lifecycle.</li><li>Collaborate with data engineering, technology, finance, marketing, pharmacy, and other stakeholders to deliver integrated solutions that meet cross-functional analytical needs.</li><li>Evaluate emerging data technologies and AI capabilities, identifying responsible ways to improve analytical scalability, accessibility, governance, and business decision support.</li><h2>Requirements</h2><li>Bachelor's degree in Computer Science, Data Engineering, Analytics, Informatics, Information Systems, Mathematics, Statistics, or a related technical or quantitative discipline, or equivalent relevant professional experience.</li><li>At least 7 years of experience in data analytics, informatics, business intelligence, data engineering, analytical engineering, or a related field, including relevant graduate or postgraduate experience.</li><li>Demonstrated experience leading complex analytical data initiatives, data product development, or analytical platform projects.</li><li>Hands-on experience working with modern cloud-based data and analytics environments.</li><li>Strong SQL skills, including experience developing complex analytical transformations, reusable queries, and reliable data assets.</li><li>Proven expertise in designing, developing, testing, and maintaining ETL/ELT pipelines.</li><li>Experience with dimensional, relational, or analytical data modeling and designing data structures that support downstream analytics and reporting.</li><li>Strong knowledge of data quality, reconciliation, testing, metadata management, data lineage, documentation, and analytical governance.</li><li>Experience working with healthcare, payer, pharmacy, claims, or other complex healthcare datasets.</li><li>Thorough understanding of data grain, source relationships, business rules, aggregations, population definitions, and the analytical implications of combining disparate datasets.</li><li>Ability to translate business definitions, KPI requirements, and analytical methodologies into scalable, repeatable technical solutions.</li><li>Demonstrated ability to troubleshoot complex data issues, identify root causes, and resolve problems across upstream and downstream data processes.</li><li>Excellent written and verbal communication skills, with the ability to explain technical architecture, data limitations, and analytical implications to both technical and nontechnical stakeholders.</li><li>Proven ability to provide technical leadership, influence standards, guide solution design, and collaborate effectively across teams.</li><li>Strong analytical thinking, attention to detail, and a commitment to data integrity, continuous improvement, and responsible technology adoption.</li><h2>Preferred qualifications:</h2><li>Master's degree in Computer Science, Data Engineering, Analytics, Informatics, Information Systems, Data Science, Statistics, or a related discipline.</li><li>Significant hands-on experience with Databricks and its associated data engineering and analytics ecosystem.</li><li>Experience developing curated data products for AI-assisted analytics, natural-language querying, or governed self-service analytical environments.</li><li>Experience configuring, implementing, or supporting Databricks Genie One or comparable AI-assisted analytics platforms.</li><li>Proficiency in Python or another programming language used for data engineering, automation, testing, or advanced analytics.</li><li>Direct experience working with pharmacy or prescription claims data, including knowledge of pharmacy business concepts and healthcare data structures.</li><li>Experience in payer, pharmacy benefit management (PBM), mail-order pharmacy, Medicare, or related healthcare environments.</li><li>Experience integrating pharmacy claims, membership, marketing, operational, and financial datasets to support cross-functional analysis.</li><li>Familiarity with enterprise KPI governance, semantic layers, reusable measures, metadata frameworks, and standardized business rules.</li><li>Experience with enterprise data catalogs, lineage tools, governance frameworks, access controls, and healthcare data privacy requirements.</li><li>Knowledge of data development lifecycle practices, including version control, code reviews, automated testing, and controlled deployments.</li><li>Experience designing analytical assets that serve data analysts, business analysts, and business users through governed self-service tools.</li><h2>Remote work requirements:</h2><li>Reliable internet connectivity with a minimum download speed of 25 Mbps and upload speed of 10 Mbps. Wired cable or DSL connections are recommended.</li><li>A dedicated home workspace that minimizes interruptions and safeguards confidential and protected health information in accordance with applicable privacy requirements.</li><li>Availability to work a full-time schedule of 40 hours per week and willingness to travel occasionally for meetings or training.</li><h2>Benefits</h2><li>
<strong>Competitive annual salary:</strong>$117,600–$161,700, depending on geographic location, qualifications, experience, education, certifications, and relevant skills.</li><li>
<strong>Performance-based bonus:</strong>Eligibility for additional incentive compensation based on individual and/or organizational performance.</li><li>
<strong>Remote work flexibility:</strong>Nationwide remote work arrangement, with occasional travel for business meetings or training.</li><li>
<strong>Medical insurance:</strong>Healthcare coverage to support employees' health and well-being.</li><li>
<strong>Dental and vision insurance:</strong>Benefits to support preventive care and overall health.</li><li>
<strong>Retirement savings:</strong>Access to a 401(k) retirement savings plan.</li><li>
<strong>Paid time off:</strong>Leave benefits to support personal needs, rest, and work-life balance.</li><li>
<strong>Paid holidays:</strong>Company holidays and personal holidays.</li><li>
<strong>Family support:</strong>Paid parental and caregiver leave to help employees manage important family responsibilities.</li><li>
<strong>Disability coverage:</strong>Short-term and long-term disability insurance.</li><li>
<strong>Life insurance:</strong>Coverage to provide additional financial protection.</li><li>
<strong>Technical leadership opportunities:</strong>Influence data architecture, analytical standards, and the development of scalable data products.</li><li>
<strong>Innovation and professional growth:</strong>Work with modern data platforms, AI-assisted analytics, and emerging technologies in a complex healthcare environment.</li><li>
<strong>Cross-functional collaboration:</strong>Partner with specialists across data engineering, finance, pharmacy, marketing, technology, and analytics.</li><li>
<strong>Meaningful business impact:</strong>Improve the quality, accessibility, and reliability of insights that support operational performance and strategic decision-making.</li>