Senior Software Engineer (Rust + Python) — Clinical Data Platform

Description

The team is building a new clinical data platform from scratch and is hiring a senior engineer to own its core data engine, which is written in Rust.

The engine pulls records from hospital systems, checks and parses them, and maps them to a standard data model that researchers and cancer registries depend on. Accuracy comes first because errors cannot be corrected later, which is why the engine uses Rust. Python and SQL handle the pipeline around it, and you will work in both.

The platform has not launched yet, so you will help shape its architecture rather than inherit one.

No healthcare background is needed. The data standards will be taught. The team wants a strong engineer who writes careful, well-tested code and can justify their decisions.

Stack: Rust for the engine, Python for the pipeline and orchestration, PostgreSQL, Terraform, AWS (ECS/Fargate, RDS, Lambda, S3), and GitHub Actions for CI/CD.

Responsibilities

• Take ownership of the Rust data engine, from design and testing through to running it in production.
• Build parsing, validation and mapping so that invalid input is refused with a clear reason and never guessed at.
• Work on the Python and SQL pipeline around the engine, including PostgreSQL schema design.
• Make the engine safe to run at scale: retries, idempotent runs so a rerun never duplicates data, and clear failure handling.
• Help set engineering standards covering types, tests, code review (including AI-generated code) and CI.
• Help decide the platform architecture while it is still being designed.

Requirements

• Required: Rust you have shipped in production, in open source, or in a substantial project of your own. Be ready to say what it does and share a link if you can.
• Required: 5+ years building backend systems or data pipelines in production.
• Required: solid Python and SQL, with PostgreSQL preferred, including schema design.
• Required: strong correctness habits, meaning typed code, tests that cover failure paths, and code review.
• Required: you use AI coding assistants productively and check their output with types, tests and CI rather than trusting it.
• Optional: data pipelines that handled retries, backfills or reprocessing.
• Optional: parsers or data-format work in any domain.
• Optional: Terraform and AWS (ECS/Fargate, RDS, Lambda, S3).
• Optional: workflow orchestration such as Airflow or Step Functions.
• Optional: healthcare data experience with FHIR, HL7 or OMOP.