Reify Health is hiring a
Staff Data Platform Engineer

Summary

Join us in our mission to advance clinical research and improve patient care. As a Staff Data Platform Engineer, you will design, build, and shape the architecture of the data pipelines and infrastructure to support a modern data lake across our organization.

Requirements

• Have 8+ years of related experience with a BS, 6+ years with a MS, or 3+ years with a PhD. Equivalent work experience may substitute
• Significant track record of delivery
• At least 4 years of professional work experience in a role at a startup company dealing with regulated data (such as healthcare)
• Deep practical experience with AWS (Redshift, S3, MSK, LakeFormation etc.), Kafka, and distributed systems
• Expertise in Clojure or Python in the context of data applications
• Demonstrated ability to rapidly develop and/or convert data science projects into modules that can be readily integrated into an existing product
• Experience with systems engineering, orchestration (e.g. Terraform), and awareness of the nuances of testing and deploying distributed data architecture at scale (particularly with probabilistic output)
• Notable open-source contributions to software used by the data engineering or data science communities

Responsibilities

• Support the development and expansion of our next-generation, privacy-aware data architecture using Kafka, AWS Lake Formation and Apache Iceberg
• Prototype new algorithms or intelligence modules to support forthcoming data products
• Support our internal and external data products by building, scaling, and integrating data ingestion and ETL processes
• Become intimately familiar with HIPAA, GDPR, and other applicable regulatory frameworks and how they influence our architecture and development decisions
• Represent the Data team to external parties
• Guide development of technical solutions of our most challenging problems and start to exert more significant influence on the Data Engineering roadmap and architecture
• Help set the standard for the team and drive best practices for high-performance, large-scale systems
• Regularly present new proposals at architectural design reviews
• Ship large features and foundational improvements with little to no guidance
• Live our data philosophy, which focuses on ethical decision making, being aware of how biased data (and assumptions) can affect results (and people), and being laser-focused on business needs