Senior Data Engineer - Implementation

Paradigm Health

5h•$150,000 - $165,000•Remote

About The Position

Paradigm is rebuilding the clinical research ecosystem by enabling equitable access to trials for all patients. Our platform enhances trial efficiency and reduces the barriers to participation for healthcare providers. Incubated by ARCH Venture Partners and backed by leading healthcare and life sciences investors, Paradigm’s seamless infrastructure implemented at healthcare provider organizations, will bring potentially life-saving therapies to patients faster. Our team hails from a broad range of disciplines and is committed to the company’s mission to create equitable access to clinical trials for any patient, anywhere. Join us, and bring your expertise, passion, creativity, and drive as we work together to realize this mission. Paradigm’s Software Engineering team builds and maintains the foundational infrastructure that powers our clinical care data ecosystem. We ingest and integrate data from diverse sources—including Electronic Health Records, lab providers, and Health Information Exchanges—and transform it through enrichment and harmonization to support a wide range of internal consumers and product verticals. As Paradigm’s footprint across patient populations, research initiatives, and health systems expands, the team is focused on scaling our architecture to enable efficient, parallel data processing at scale. As part of the Data Core team, you’ll work with the engineering team and our commercial counterparts to ingest patient data into our system and build reusable platforms. You will partner closely with product, design, and other internal engineering teams to build resilient features, address bugs, and collaborate to plan upcoming work.

Requirements

You bring experience building data pipelines and working with ETL systems (DBT, Airflow, Dagster, or similar).
You are proficient in SQL and have worked with a data warehouse system (we use Databricks).
You have experience programming in Python and a compiled language like Java.
You’ve worked with big data technologies such as Kafka and Spark.
You understand data pipelines and how to design them for reliability and scale.

Nice To Haves

experience with healthcare data formats such as HL7 or FHIR.

Responsibilities

Production readiness - handle a moderate size release, know what it means to monitor it and communicate it.
Designs and implements solutions using best practices, drives architecture decisions for their team.
Proactively consider cross team effects of their work, breaks down work and drives with the appropriate stakeholders.
Proactively communicates updates on progress and blockers to ensure timelines can be met and adjusted accordingly.
Effectively communicate within your team and other teams.
Share and promote best practices to help your teammates grow.
Understands the product area you are working with, and how it is used in context of the overall product.
Works on epics on the scale of ~ 3 months
Partner with our customer teams to develop engineering plans to implement our health system partners
Build and support robust batch and streaming pipelines
Build tools and processes to make data accessible across products and data consumers
Evolve the maturity of our monitoring systems and processes to improve visibility and failure detection in our infrastructure
Become a subject matter expert on our different datasets and tooling