Data Engineering Lead

About the role

About RhythmX AI

RhythmX AI is a generative AI-native health company driving a paradigm shift in hyper-personalized care. RhythmX AI’s precision care platform helps physicians pioneer a new era of whole-person care through generative and predictive AI-powered copilots. An SAIGroup company, RhythmX AI leverages SAIGroup assets, including the advanced Eureka AI platform and longitudinal data related to 300 million patients, more than 4.4 billion total annual claims, and more than 1.8 million healthcare professionals at more than 300 thousand facilities. RhythmX AI comprises healthcare and technology experts, operators, and the industry’s leading clinical advisors. https://rhythmx.ai/

Job Overview

We are seeking an experienced Data Engineering Lead with a solid foundation in Python, MongoDB, PostgreSQL, Apache Airflow and other data management tools to join our innovative team. This role is critical for building and managing robust data pipelines that extract and process data from health system EHR systems, supporting our AI-driven healthcare applications.

Key Responsibilities:

- AI Infused Data Pipeline Construction: Develop and optimize data pipelines for the efficient extraction, transformation, loading and management of large-scale healthcare and clinical guidelines data.

- Healthcare Data Handling: Manage sensitive healthcare data adhering to FHIR, HL7 standards, as well as the version and variability of Epic Clarity extracts, Quality Measures, Drug Formularies and Clinical Guidelines ensuring compliance with data regulations and client needs.

- Data Orchestration: Use Airflow, Temporal or other similar AI-native next generation tools to manage complex data and knowledge workflows essential for processing healthcare data at scale. This includes RAG, GraphRAG, Tool calling, MCP and other AI enabled Data Orchestration, Search, Retrieval and Aggregation.

- Assessments and Collaboration: Support data scientists and backend developers by integrating and maintaining data systems across the organization. As well as in assessment and validation of large-scale Gen-AI based systems using tools such as RAGAs, Opik etc.

- Innovative Problem-Solving: Apply technical skills to address unique challenges in the healthcare sector, contributing to solutions that enhance patient care.

Minimum Qualifications

- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field.

- 10+ years of experience in data engineering, with proficiency in Python, PostgreSQL or other variant, MongoDB and Milvus Vector DB.

- Experience building and managing data pipelines using healthcare data from hospital EHR systems and other clinical data sources such as HIEs and clinical standards bodies (CMS, NCQA etc).

- Demonstrated experience with data lakes, ensuring robust and scalable data storage solutions.

Highly Preferred Qualifications

- Azure technology stack expertise to improve data processing and storage capabilities.