Role Description Essential Job Functions: - Design, develop, and maintain scalable data models that support enterprise reporting, analytics, and operational decision-making. - Build, optimize, and maintain robust ETL/ELT pipelines using modern data transformation frameworks. - Develop and maintain curated datasets that improve data accessibility, consistency, and usability across business domains. - Partner with business stakeholders to gather requirements and translate business needs into scalable analytical solutions. - Lead efforts to improve data quality through validation, testing, monitoring, and implementation of data governance best practices. - Monitor and troubleshoot production data pipelines, proactively identifying and resolving performance or reliability issues. - Develop reusable SQL and Python-based solutions to automate data transformations and reporting processes. Other Job Functions: - Understand, adhere to, and implement the Company's policies and procedures. - Build collaborative relationships with business and technical stakeholders across the organization. - Drive continuous improvement by identifying opportunities to automate, standardize, and optimize analytics workflows. - Communicate technical concepts effectively to both technical and non-technical audiences. - Demonstrate accountability, initiative, and ownership of project deliverables. - Stay current with emerging technologies and industry best practices in analytics engineering and healthcare analytics. - Support cross-functional projects and contribute to strategic enterprise analytics initiatives. Qualifications - Minimum Experience: 4–7 years of experience developing analytics solutions, data transformation pipelines, or enterprise reporting platforms. - Advanced proficiency in SQL, including performance optimization and complex query development. - Strong proficiency in Python or similar programming language for data transformation and automation. - Experience designing and maintaining dimensional data models and curated analytical datasets supporting Medicare Advantage, value-based care, population health, or healthcare operations. - Experience working with modern ETL/ELT methodologies and production data pipelines. Requirements - Preferred Experience: Experience with cloud data platforms such as Snowflake, SQL Server, or similar modern data warehouses. - Strong experience with DBT or comparable data transformation frameworks. - Experience using VS Code, Git/Bitbucket, and CI/CD development practices. - Experience implementing automated data quality testing and monitoring. - Experience mentoring junior team members and participating in technical design discussions. Education - Bachelor's degree in Mathematics, Computer Science, Statistics, Engineering, Information Systems, or a related field required. - Master's degree preferred but not required. Skills and Abilities - Strong ability to translate complex business requirements into scalable and maintainable data models. - Advanced SQL development and query optimization skills. - Strong understanding of dimensional modeling, data warehousing principles, and modern analytics engineering practices. - Experience designing reliable, scalable, and well-documented data pipelines. - Strong analytical and problem-solving abilities with excellent attention to detail. - Ability to independently prioritize multiple projects in a fast-paced environment. - Excellent written and verbal communication skills with the ability to communicate effectively across technical and business audiences. - Ability to mentor junior engineers and contribute to team technical growth. - Passion for continuous learning and improving healthcare through data and analytics. Compensation The posted salary range reflects the anticipated base salary hiring range only. Final compensation will be based on experience, expertise, location, internal equity, and business needs. Candidates with exceptional experience may be considered within the broader compensation range, where appropriate. Location: Remote - MA Pay Range: $100,000.00 - $122,600.00 Salary range shown is a guideline. Individual compensation packages can vary based on factors unique to each candidate, such as skill set, experience, and qualifications.

• Design and ship full-stack features across our TypeScript frontend and TypeScript Lambda backends. • Model data and metrics in Cube.dev; build embedded analytics experiences using Embeddable components. • Own the production lifecycle of your features: CI/CD, performance, observability, and post-deploy validation. • Implement your own AWS infrastructure (Lambda, IAM, networking, storage) using Terraform; we have a dedicated AWS engineer who will review and partner with you on the harder pieces. • Work day-to-day in Claude Code and contribute to the team's AI context library, prompts, and process improvements. • Pair with our designer, data engineers, and dashboard configuration lead to land features that hold up against real customer data.

• Works with end-user requests to detail moderately to sophisticated business requirements, data definitions, business rules, and data quality requirements support of enterprise data intelligence projects. • Creates specifications for reports and analysis based on business/clinical needs and data elements required or available. • Produces data sets, reports, ad-hoc requests, dashboards, etc. • Conducts data analysis in support of a variety of analytic solutions. • Provide the specialized expertise needed to build, validate, and operationalize AI and analytics solutions in a secure healthcare environment. • Supports Azure Fabric migration by developing reusable data models, pipelines, semantic layers, AI-ready datasets, and governance-aligned reporting assets. • Accelerate delivery of predictive analytics, natural language processing, automation, anomaly detection, and self-service intelligence to reduce manual analysis, surface risks earlier, and improve decision speed across the organization.

• Perform enterprise-level statistical analysis to investigate trends, patterns, and relationships using statistical methods/tests to reach actionable conclusions. • Develop, train machine learning models to apply algorithms that support predictive analytics, classification tasks (e.g., land cover change), and operational forecasting • Develops enterprise-level information technology solutions by analyzing, coding, testing, and implementing new software and by modifying/enhancing existing software applications. • Coordinates with business analysts and/or users to determine requirements. Performs moderately complex analyses of system requirements and of existing business processes and information systems. • Collaborates with architects to determine the design of quality technical solutions. • Reviews systems under development and related documentation. • Resolves customers’ issues and responds to suggestions for improvements and enhancements. Participates in the development of software. • Performs code reviews and assists in more complex systems planning, scheduling and implementation.