[Hiring] Senior Analytics Engineer @Clover Health

Role Description

The Clover Care Services organization delivers proactive support and care to our members through our Clover Home Care teams, and quality improvement services to our aligned insurance plan providers through our practice engagement team. We have built one of the most proactive, data-driven health care services platforms in New Jersey and are excited about the future of technology and how it impacts our ability to bring transformative results to both patients and providers.

As a Senior Analytics Engineer in the Clover Care Services (CCS) organization, you will design and build the data foundation that powers CCS analytics and AI initiatives. This role is centered on data modeling, table development, and deployment of production-ready tables to the clinical data warehouse. You will mine and extract data from Athena EMR through the Athena Dataview, and assess, cleanse, and organize clinical, claims, and operational data so it is properly structured in the clinical data warehouse for consumption by downstream reporting tools and AI engines. You will partner with clinical and operational stakeholders, as well as data science and AI teams, to ensure the warehouse is built on reliable, well-modeled, and well-documented data.

The right person must be a data-driven, highly analytical builder with exceptional organizational skills, strong data modeling instincts, and a passion for building the data infrastructure that lets AI and analytics teams draw insights with confidence.

As a Senior Analytics Engineer, you will:

• Design and develop conceptual, logical, and physical data models for clinical, claims, pharmacy, and EMR data to support the clinical data warehouse.
• Build, test, and deploy new and modified tables, views, and schemas to the clinical data warehouse, following established data modeling and warehousing standards.
• Mine, extract, and validate data from Athena EMR through the Athena Dataview, translating clinical source data into warehouse-ready structures.
• Assess, cleanse, and organize data from disparate sources (claims, lab, pharmacy, EMR, and operational systems) so it can be reliably structured and integrated into the clinical data warehouse.
• Partner with AI, machine learning, and data science teams to structure and document warehouse tables so AI engines can efficiently access data and surface accurate insights.
• Develop and maintain complex SQL, ETL/ELT logic, and stored procedures to transform raw source data into curated, analysis-ready tables.
• Establish and maintain data modeling standards, data dictionaries, naming conventions, and lineage documentation for the clinical data warehouse.
• Ensure data accuracy, quality, and integrity across the warehouse through validation routines, testing, and ongoing monitoring of table deployments.
• Gather requirements from clinical, operational, and analytics stakeholders and translate them into data model designs and technical specifications.
• Prepare and present data architecture, data model, and warehouse deployment recommendations to leadership and technical stakeholders in support of Clover Care Services business initiatives.

Success in this role looks like:

• In your first 90 days, you will:
  • Learn the intricacies of the Athena EMR data, the Athena Dataview, and the other data sets that feed the clinical data warehouse.
  • Build and deploy your first set of data models and tables to the clinical data warehouse.
  • Document data modeling standards and warehouse table conventions for the CCS team.
• After 6 months you will:
  • Partner with stakeholders to design and implement a scalable data model for mining and structuring Athena EMR data via the Athena Dataview.
  • Deploy a robust set of curated, AI-ready tables to the clinical data warehouse that support both reporting and AI-driven insight generation.
• Future success in this role includes:
  • Data Foundation: Serve as the architect of a well-modeled, well-governed clinical data warehouse that reliably powers analytics and AI engines across CCS.
  • Organizational Development: Foster a culture of strong data modeling practices, documentation, and continuous improvement within the organization.

Qualifications

• A BA/BS in Computer Science, Data Engineering, Mathematics, Statistics, Healthcare Informatics, or a related discipline, with 5+ years of relevant professional experience.
• Hands-on experience with data modeling (conceptual, logical, and physical) and dimensional/warehouse design (e.g., star schema, snowflake schema, data vault).
• Proven experience developing, testing, and deploying tables, views, and ETL/ELT pipelines into an enterprise or clinical data warehouse.
• Direct experience mining and extracting data from Athena EMR, including working with the Athena Dataview or comparable EMR reporting/extract tools.
• Strong SQL proficiency and hands-on Python experience, including using Python to query, transform, validate, and automate workflows involving large, complex healthcare datasets (claims, lab, pharmacy, and EMR).
• Working knowledge of Git and GitHub for version control, code review, pull requests, documentation, and collaborative development workflows.
• Experience assessing and organizing disparate healthcare data sources into clean, standardized, well-documented data structures suitable for downstream analytics and AI/ML consumption.
• Familiarity with data governance practices, including data dictionaries, metadata management, lineage tracking, and data quality validation.
• Knowledge of healthcare data standards and coding systems (ICD-10, CPT, DRG) and familiarity with healthcare quality measures (e.g., HEDIS, CMS, NCQA), preferably within Medicare Advantage.
• Exposure to how AI/ML engines and analytics platforms consume structured data, and an interest in designing data models that make insight generation easier for those systems.
• Strong communication skills with the ability to translate complex data architecture and modeling decisions into clear guidance for clinical, technical, and operational stakeholders, using tools such as Excel and data visualization platforms.

Benefits

• Financial Well-Being: Competitive base salary and equity opportunities, performance-based bonus program, 401k matching, and regular compensation reviews.
• Physical Well-Being: Comprehensive medical, dental, and vision coverage.
• Mental Well-Being: Initiatives such as No-Meeting Fridays, monthly company holidays, access to mental health resources, and a generous flexible time-off policy.
• Professional Development: Learning programs, mentorship, professional development funding, and regular performance feedback and reviews.
• Additional Perks:
  • Employee Stock Purchase Plan (ESPP) offering discounted equity opportunities.
  • Reimbursement for office setup expenses.
  • Monthly cell phone & internet stipend.
  • Remote-first culture, enabling collaboration with global teams.
  • Paid parental leave for all new parents.
  • And much more!