Data Architect, Clinical

Why Prolaio?

• Impactful Work: You will join in the fight against heart failure (HF) and hypertrophic cardiomyopathy (HCM) with the goal of extending and saving the lives of our patients while also being at the forefront of changing the healthcare industry through technology.
• Innovative Environment : You will be part of an organization doing something that’s never been done before.
• Professional Growth : You will join a growing team and have a substantial impact on our daily and future operations with the opportunity to continuously learn and grow.
• Collaborative Team : You will be part of a team of collaborative, curious, and committed individuals focused on the collective good, inclusiveness, scientific excellence, and advancing digital health for cardiology.

Who You Are?

• Bachelor’s degree in computer science, Data Engineering, Information Systems, Biomedical Informatics, Engineering, or a related field.
• Minimum 10 years of experience in healthcare, life sciences, medtech, digital health, or other patient-data-focused environments, including at least 5 years in clinical data, real-world data, clinical trials data, or other patient-centered data platforms.
• Demonstrated experience architecting healthcare data platforms that support structured, semi-structured, and unstructured data in regulated or validated environments.
• Deep understanding of data from cardiology focused wearables devices, claims, socioeconomic, behavioral, and EHR.
• Deep understanding of healthcare data domains, data modeling, standardization, normalization, and the application of healthcare terminologies and common data models.
• Strong experience working in a cross-functional, matrixed organization and partnering effectively with Product, Engineering, Data Science, Analytics, Clinical Operations, Quality, and Security teams, with the ability to operate as a self-starter in a growth-stage environment.
• Strong familiarity with cloud platforms such as GCP, AWS, or Azure and modern data platforms such as Snowflake, Databricks, BigQuery, Redshift, Synapse, or comparable environments.
• Experience with ETL or ELT, orchestration, and large-scale data processing tools such as dbt, Airflow, Dagster, Spark, Kafka, Fivetran, Informatica, Talend, or similar technologies.
• Strong SQL and Python skills, with familiarity in APIs, event-driven architectures, interoperability frameworks, and clinical data exchange patterns such as HL7 and FHIR
• Familiarity with metadata, lineage, catalog, governance, and AI-enablement tools, including platforms for semantic indexing, vectorization, retrieval, and data lifecycle automation.