Senior Data Platform & Operations Engineer

Senior Data Engineer

This company operates a cardiovascular performance improvement platform used by 30+ health system partners across the United States. They ingest clinical registry and administrative hospital data, calculate hundreds of quality measures and benchmarks at a granular level, and help cardiovascular service lines understand how they compare to national peers and where improvement opportunities exist. Their work directly impacts both patient outcomes and hospital performance.

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.

This role reports directly to the CTO. It is designed for someone who wants to build, fix, and improve systems with minimal oversight and lead through example.

Responsibilities:

• Migrate existing PySpark pipelines to Ibis / DuckLake on the Ascend Gen3 platform
• 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
• 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
• 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
• 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
• 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.