A remote Data & ML role at Imagine Pediatrics.
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Original listing text, shown exactly as published by the company.
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.
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 systems (e.g., webhooks, asynchronous processing, or CDC patterns).
Experience with data orchestration tools such as Dagster (or similar).
Experience working with infrastructure-as-code (Terraform), primarily extending and adapting existing modules and patterns.
Experience with cloud data warehouses, preferably Snowflake, including performance-aware SQL development.
Proficiency in at least one scripting language beyond SQL and Python (JavaScript, TypeScript, or Go) for automation, tooling, or serverless functions.
Demonstrated use of modern software engineering practices including version control, CI/CD, testing, and code review.
Proven ability to troubleshoot complex data and infrastructure issues across multiple systems and clearly communicate findings to both technical and non-technical stakeholders.
Proven ability to reason about downstream analytical impact of data pipeline design, including data freshness, grain, and transformation behavior.
Experience working closely with analytics engineering, data modeling, or similar downstream consumers of data.
Experience designing or managing IAM policies and least-privilege access models across data platform services.
Experience with dbt or modern analytics engineering workflows.
Experience working with healthcare data, FHIR resources, or clinical systems
Familiarity with HIPAA compliance and handling of PHI in cloud environments.
Experience with high-volume ingestion systems including webhook-based tools (e.g., Hevo, Fivetran, or similar).
Experience driving the adoption of AI tools to improve engineering productivity.
Exposure to real-world evidence (RWE), health economics and outcomes research (HEOR), or similar evidence-generation programs.
Imagine Pediatrics
Data & ML
40 open roles on Sydicom
Imagine Pediatrics delivers home-based medical and supportive care services for children with complex or chronic conditions. The company focuses on enhancing quality of life for pediatric patients and their families through an interdisciplinary approach to palliative care.
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