Permanent
Posted on 06 March 26 by Maci Pantoja
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About the Role:
They are looking for a senior individual contributor who ships quickly, thinks independently, and uses AI tools as a force multiplier. This is a high-autonomy, hands-on engineering role focused on owning critical data pipelines end to end, from ingestion through transformation to production delivery, while also helping manage cloud infrastructure and DevOps operations.
● Build and maintain disease-state-specific measures pipelines
● Build and maintain the cross-tenant benchmarks pipeline
● Build and maintain an Echo NLP pipeline that extracts structured data from unstructured echocardiogram narrative text
● Work across the full pipeline lifecycle: design, implementation, testing, deployment, and monitoring Data Quality & Testing
● Expand test coverage and improve testing harnesses and related infrastructure
● Fix noisy and flaky test suites that generate false positives
● Add new test types, including browser-based tests and full pipeline validation runs
● Help establish a testing culture where tests are meaningful, not ceremonial
DevOps & Infrastructure
● Manage Azure cloud infrastructure
● Interface with the MSP on business and technical issues
● Implement and maintain Infrastructure as Code using Bicep / Terraform
● Enforce RBAC and least-privilege access policies
● Monitor and optimize cloud costs
Data Operations
● Improve and automate data ingestion, movement, and recovery processes
● Build toward reliable, rollback-capable release cadences
● Reduce manual operational steps
● Make data operations more observable and repeatable
AI-Augmented Development
● Use AI coding tools such as Claude Code, Cursor, or similar in daily workflow
● Contribute to an AI-forward engineering culture focused on faster iteration, better code quality, and stronger testing
Requirements:
● 7+ years of data engineering or platform engineering experience
● Deep Python and SQL proficiency
● Experience with PySpark
● Ideally experience with Ibis or other dataframe abstraction layers
● Experience with DuckDB
● Experience working at a healthcare SaaS startup
● Azure cloud experience, or strong AWS / GCP experience with the ability to ramp quickly
● Experience with Kubernetes and Docker
● Experience with data quality frameworks such as Great Expectations, dbt tests, or similar
● Active, proficient use of AI coding tools in daily work
● Self-directed working style with the ability to identify problems and solve them without constant direction
Nice to Have Skills:
● Healthcare data experience, including clinical registries, HIPAA, or Safe Harbor de-identification
● Experience with DuckLake
● Experience with Ascend.io or similar pipeline orchestration platforms
● Experience collaborating with offshore engineering teams across time zones
● Experience with Infrastructure as Code tools such as Terraform, Bicep, or CloudFormation
What The Company Offers:
● Fully remote, US-based role
● Small team, high impact
● Work that directly affects how hospitals improve patient care
● Direct access to the CTO
● Influence over architectural decisions
Note on AI This is an AI-forward engineering team. They expect engineers to actively use AI tools in their daily work. They view AI-assisted development as a force multiplier for experienced engineers and want people who use these tools thoughtfully and effectively, not as shortcuts.