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Who We Are Imagine Pediatrics is a tech enabled, pediatrician led medical group reimagining care for children with special health care needs. We deliver 24/7 virtual first and in home medical, behavioral, and social care, working alongside families, providers, and health plans to break down barriers to quality care. We do not replace existing care teams; we enhance them, providing an extra layer of support with compassion, creativity, and an unwavering commitment to children with medical complexity. What You’ll Do   As a Staff Data Engineer at Imagine Pediatrics, you will be the first dedicated Data Engineer on a hybrid team with Analytics Engineers, responsible for defining how data moves through our platform and owning the data pipelines that power clinical analytics, operational reporting, and external integrations.   You will ensure that data ingestion and integration decisions are made with a clear understanding of downstream analytical usage, including how data freshness, grain, and structure impact downstream processes and systems. You will partner closely with Analytics Engineers, Product Engineers and Platform Engineers to deliver a platform built for a high-growth, mission-driven healthcare organization. This role requires strong technical depth in data engineering, comfort operating in ambiguous problem spaces, and the ability to influence across engineering and product teams.   Design, build, and maintain scalable ELT pipelines that ingest data from clinical systems, APIs, and third-party integrations utilizing webhook-based, API-based, and CDC (change data capture) approaches.   Architect and manage event-driven data pipelines in AWS — including cross-account configurations and dead-letter queue handling.   Write and maintain infrastructure-as-code to deploy and manage data ingestion workloads, primarily extending existing modules and patterns.   Orchestrate pipeline execution and monitoring using Dagster, ensuring observability and reliability across all workflows.   Implement data quality checks, alerting, and lineage tracking across the pipeline.   Identify and eliminate systemic failure modes in pipelines, improving reliability through long-term fixes rather than repeated incident remediation.   Partner with Analytics Engineers to ensure upstream data supports correct and consistent downstream models.   Set technical direction for data architecture and mentor other engineers.   What You Bring & How You Qualify   You are driven by curiosity and committed to reimagining pediatric healthcare — creating a world where every child with complex medical conditions gets the care and support they deserve. You thrive in a fast-paced startup environment and bring both engineering depth and a collaborative mindset. You enjoy owning systems end-to-end, thinking in systems, not just pipelines, and are comfortable working across infrastructure, data movement, and analytics workflows.   You are proactive, collaborative, and not afraid to push back on unclear assumptions. You communicate tradeoffs clearly and help teams make better technical decisions. You will need Required   7–10+ years of data engineering or platform engineering experience, including at least 2+ years in a senior or staff-level role owning production data systems.    Strong experience designing data pipelines using Python and SQL.    Strong experience with AWS services including Lambda, SQS, SNS, and S3.    Strong experience building event-driven and API-based ingestion