Staff Data Platform Engineer

Summary

Join OneStudyTeam, a Reify Health company, and contribute to building a data platform for reporting and AI insights. As a Staff Data Platform Engineer, you will design, build, and shape the architecture of data pipelines and infrastructure for a modern data lake. You'll work directly with sponsors and external parties on data products focused on accelerating clinical trial enrollment. This fully remote position (India only) requires expertise in AWS, Kafka, and distributed systems, along with experience in regulated data environments. You will play a key role in shaping the data engineering roadmap and architecture, ensuring ethical data practices, and contributing to large-scale system improvements.

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)

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

Preferred Qualifications

Notable open-source contributions to software used by the data engineering or data science communities