Senior Data Engineer – Healthcare Data & AI Systems

5+ years of experience in data engineering or backend systems, with senior or staff-level contributions. Deep Python proficiency, with production experience in ETL, data validation, and orchestration frameworks (e.g., Airflow, Dagster, dbt). Strong experience with data warehouse design, including star/snowflake schemas, denormalization strategies, and performance optimization. Strong understanding of data privacy and security practices, especially in healthcare (HIPAA, de-identification, audit logging, etc.). Proven experience managing complex integrations with EMRs or clinical systems. Familiarity with LLM and ML development tools (e.g., TensorFlow, PyTorch, LangChain, transformers, vector DBs). Experience deploying or supporting predictive models in production environments. Expertise in Snowflake or similar cloud data platforms (e.g., BigQuery, Redshift). Strong grasp of data modeling, provenance, and semantics for analytical and AI purposes. Experience working with AWS services such as S3, Lambda, Batch, Event Bridge, Cloud Front, EC2, etc.

Architect and implement robust data pipelines between EMRs, internal systems, and Snowflake. Lead the design of warehouse schemas for transactional processing, reporting (BI), and statistical/ML analysis. Define and enforce standards for data semantics, integrity, quality, lineage, and access control. Collaborate with data scientists and ML engineers to enable production-grade ML workflows. Experiment with and support the deployment of LLMs for reasoning, summarization, and classification. Build monitoring and alerting around pipeline health and data trustworthiness. Integrate and normalize complex healthcare data sources into a unified analytics model. Partner with engineering and product teams to deliver data-driven features, dashboards, and insights.