Specialist, Analytics Engineer

Job Description Data Strategy Products and Solutions, Digital Human Health (DHH) About the Role Our Digital Human Health (DHH) organization is transforming how data is leveraged to improve patient outcomes, enhance healthcare experiences, and enable data-driven decision-making across Human Health. Within DHH, the Data Strategy, Products & Innovation (DSPI) team builds scalable data products that power analytics, reporting, advanced insights, and AI-driven solutions across the patient support ecosystem. As an Analytics Engineer, you will design, develop, and support analytical data products that provide visibility into the end-to-end patient journey across Patient Support Services (PSS), Specialty Pharmacy (SP), Hub Operations, Hub Enrollment, and Aggregator data ecosystems. You will partner with Data Product Owners, analytics teams, data engineers, and business stakeholders to transform complex healthcare data into trusted, scalable, and business-ready datasets supporting patient access, therapy initiation, fulfillment, adherence, persistence, and patient support analytics. Primary Responsibilities Data Product Development and Engineering Hands-on development of last-mile data products using the most up-to-date technologies and software / data / DevOps engineering practices · Build and maintain analytical data products supporting Patient Support Services, Specialty Pharmacy, Hub Enrollment, Aggregator, and Patient Journey analytics. · Develop scalable data pipelines, automated data models, curated datasets, and semantic layers for reporting, analytics, data science, and AI use cases. · Translate requirements and user stories from Data Product Owners and Lead Analytics Engineers into development activities across design, build, testing, deployment, and support. · Integrate patient-level data across multiple healthcare sources and create reusable, business-ready datasets with consistent definitions and measures. Patient Journey and Healthcare Analytics · Enable analytics across the pre- and post-prescription patient journey, including enrollment, benefits verification, prior authorization, therapy initiation, dispense and fulfillment, adherence, persistence, and patient support program engagement. · Support datasets and measures that provide insight into patient access barriers, enrollment-to-treatment conversion, time to therapy, therapy progression, abandonment, discontinuation, and patient retention. · Experience on working with data designing and integrations for Affordability (Copay/PAP/Bridge, Quick Start) and Adherence (Nurse Navigator, Digital Platforms) · Develop working knowledge of Hub, Specialty Pharmacy, Aggregator, claims, and patient services data, including source-specific limitations, business rules, and reconciliation needs. · Partner with analytics and business teams to define and standardize patient journey milestones, KPIs, cohorts, and business definitions. Data Quality, Governance and AI Readiness Ensure data products are developed with governance, privacy, compliance, quality, lineage, and documentation by design. Perform data profiling, validation, reconciliation, and root-cause analysis across Hub, Specialty Pharmacy, Aggregator, and related patient-level data sources. Ensure data products are trusted, scalable, reusable, and fit for analytical and AI-driven consumption. Collaborate with cross-functional product squads and communicate data risks, dependencies, and delivery progress clearly to technical and non-technical stakeholders. Work within Agile delivery frameworks and contribute to backlog refinement, estimation, testing, release readiness, and continuous improvement. sessions, and capability enablement. Required Experience and Skills 5+ years of relevant experience in analytics engineering, data engineering, healthcare analytics, or a related discipline, preferably within the pharmaceutical, biotechnology, healthcare, or patient services industry. Experience with Patient Support Services, Specialty Pharmacy, Hub, Hub Enrollment, Aggregator, patient claims, or related patient-level healthcare datasets. Working understanding of the patient access and patient journey lifecycle, including enrollment, benefits investigation, prior authorization, therapy initiation, fulfillment, adherence, persistence, and post-prescription support. Strong proficiency in SQL and Python, with experience building and optimizing analytical data models and pipelines. Experience with cloud-based data platforms and storage/compute services such as Databricks, Snowflake, Azure, AWS, Redshift, or equivalent technologies. Experience creating data models for reporting, visualization, data science, and advanced analytics use cases, including feature engineering where relevant. Knowledge of data quality, metadata management, governance, lineage, and privacy principles for sensitive patient-level data. Ability to understand requirements provided by Data Product Owners and Lead Analytics Engineers and translate them into reliable technical solutions. Strong analytical, problem-solving, interpersonal, and communication skills, with the ability to build productive relationships across a matrixed environment. Preferred Experience and Skills Experience supporting patient access, affordability, adherence, persistence, patient services, or specialty product analytics use cases. Knowledge of Specialty Pharmacy networks, Hub Operations, patient services vendors, Aggregator platforms, and pharmaceutical patient data ecosystems. Familiarity with healthcare data standards, patient identity and linkage considerations, de-identification, and compliant use of patient-level data. Experience with modern data stack, orchestration, transformation, cataloging, and low-code analytics tools. Experience with Power BI, ThoughtSpot, or other visualization and self-service analytics platforms. Experience enabling advanced analytics, AI/GenAI use cases through governed and reusable data foundations. Experience working in Scrum, SAFe, or other Agile delivery models. Cloud or modern data technology certifications are an advantage. Required Skills: Business Analysis, Business Intelligence (BI), Data Access, Data Compliance, Data Creation, Data Delivery, Data Engineering, Data Governance, Data Management, Data Modeling, Data Quality Control, Data Security, Data Standards, Data Strategies, Data Visualization, Healthcare Analytics, Health Information Systems (HIS), Measurement Analysis, Python (Programming Language), Snowflake (Platform), SQL Databases, Stakeholder Relationship Management, Structured Data, Use Cases, Waterfall Model Preferred Skills: Current Employees apply HERE Current Contingent Wo