Paradigm Health is rebuilding the clinical research ecosystem to enable equitable access to trials for all patients. In this role, you will lead high-impact initiatives to shape the evolution of Paradigm’s data platform, partnering with various teams to deliver scalable, AI-driven solutions.
Responsibilities:
- Lead the design and evolution of a scalable, multi-product data platform capable of supporting rapid growth (e.g., 600K to 2.5M+ patients) and expansion into new therapeutic areas
- Drive large, cross-team engineering initiatives end-to-end—from architecture and planning through production—while owning dependencies, aligning stakeholders, and ensuring predictable delivery timelines
- Architect, build, and optimize robust batch and streaming data pipelines with a focus on scalability, reusability, and enabling downstream team ownership
- Modernize legacy systems into future-state, AI-first data infrastructure by defining best practices, improving observability, and advancing monitoring and failure detection capabilities
- Partner closely with data science, product, and commercial teams to deliver reliable, AI-driven data solutions, ensuring alignment across product areas and enabling high-confidence integrations and outcomes
- Deeply understand your product area, and how it impacts other product areas to effectively propose changes and how it impacts the success of the company
Requirements:
- 7+ Years of experience in Data or Software Engineering
- Bachelor's degree in CS
- Experience with ETL systems like DBT, Airflow and Dagster
- A strong knowledge of SQL and have worked with a data warehouse system. We use Databricks at Paradigm
- Experience with python and a compiled language like Java or Kotlin (i.e. JVM)
- Working experience with building pipelines with Kafka, Spark, and other big data technologies
- Experience building infrastructure using major cloud providers e.g. AWS and infrastructure as code solutions e.g. Terraform
- Master's degree preferred
- Nice to have: You understand data and the pitfalls associated with it. You may have experience in working with HL7, FHIR or similar types of industry proprietary data feeds