Data Engineer

Seeking an experienced Data Engineer to support and extend existing data ingestion and pipeline frameworks within a modern data platform environment. This role focuses on operating and enhancing established systems rather than redesigning or re‑architecting the platform.The Data Engineer will work as part of an internal scrum team and receive work primarily from platform leads and architects. The role emphasizes distributed data processing, production‑grade pipelines, and software engineering best practices.Key ResponsibilitiesOperate and extend an existing metadata‑driven ingestion framework (MDIF)Support new data source discovery and onboardingBuild and maintain scalable data pipelines using Databricks and PythonPrepare data for analytics, reporting, and future AI/ML use casesCollaborate within an internal agile scrum team following established frameworksFollow software development lifecycle practices, including version control and CI/CDRequired Technical SkillsDatabricks (critical)PythonModern data engineering and big data experience with distributed data processingGitHub experience, including: Feature branchingCI/CD pipelinesSoftware development lifecycle practicesCloud & Platform EnvironmentAWS is the underlying cloud infrastructureDatabricks expertise is prioritized over general cloud specializationHealthcare Domain Required Experience Payer‑side healthcare experienceFamiliarity with one or more of the following: Claims dataMedicare Advantage and MedicaidACO and value‑based care modelsSTAR ratings and quality metricsRegulatory and compliance‑driven reportingOverviewRole is generally not customer‑facingSome interaction may occur for senior contributors or lead‑level responsibilitiesThis is not an entry‑level positionThis is not an over‑engineered architect roleIdeal candidates are hands‑on practitioners who can be productive quickly within established platforms