Senior Platform Data Engineer

Emploi pas sur LinkedIn

🕒 il y a 3 mois

🔔 Pennsylvania – Distant

🔔 Pennsylvania – Remote

⏰ Temps Plein

🟠 Senior

🚰 Ingénieur Data

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Geisinger

Site WebLinkedInTous les Emplois

10 000+ employés

Fondée en 1915

🏥 Santé

💊 Pharmaceutique

🧘 Bien-être

Healthcare • Pharmaceuticals • Wellness

Geisinger est une organisation de santé qui dessert les communautés de Pennsylvanie depuis plus d'un siècle, fournissant des services médicaux essentiels et des solutions de santé innovantes. L'organisation met l'accent sur la diversité, le développement de carrière et la création d'un environnement de soutien pour ses employés, tout en s'efforçant d'améliorer la santé et le bien-être de ses patients grâce à divers programmes et initiatives communautaires. Geisinger est reconnu comme l'un des systèmes de santé les plus innovants, et s'engage à façonner l'avenir de la santé en se concentrant sur les soins aux patients et l'inclusivité.

Description

• The Senior Platform Data Engineer owns roadmap, priorities, platform standards, and architecture reviews; provides formal input on performance reviews. • This position makes clinical data ready for AI at scale: owning the shared data products, retrieval infrastructure, and platform administration that the entire AI portfolio depends on. • Owns Real-time data feeds. Reusable clinical data models and feature pipelines. RAG retrieval infrastructure (ingestion, chunking, embeddings, vector DB, retrieval pipelines). • Streams data from Epic SDE, ADT feeds, lab results, and other clinical sources into Databricks for downstream model consumption. • Curates shared clinical feature tables (patient demographics, labs, vitals, diagnoses, utilization history, imaging metadata) in Databricks/Unity Catalog that multiple AI programs consume for model training, validation, and monitoring. • Designs and operates document ingestion pipelines: normalizing clinical documents, policies, guidelines, and unstructured data sources into formats ready for embedding and retrieval. • Implements and optimizes chunking strategies tailored to healthcare content (e.g., preserving clinical note structure, section-aware chunking for guidelines and protocols). • Establishes data quality gates for RAG: automated profiling, completeness checks, and accuracy scoring before content enters the vector store.

🎯 Exigences

• 5+ years in data engineering, with strong experience building both batch and streaming data pipelines • Expert-level Databricks skills: Delta Live Tables, PySpark, Unity Catalog, Feature Store • Hands-on experience with real-time data ingestion (Kafka, Spark Structured Streaming, or comparable frameworks) • Strong SQL and Python (pandas, PySpark) skills for data transformation and feature engineering • Experience administering Databricks workspaces: cluster policies, compute management, access controls, cost monitoring • Familiarity with clinical data models and healthcare data sources (EHR extracts, ADT feeds, lab results, claims data) strongly preferred • Experience with Epic data extraction methods (SDE, FHIR, epic-ws) a significant plus • Understanding of data governance principles: lineage, quality monitoring, access controls.

🏖️ Avantages

• We offer healthcare benefits for full time and part time positions from day one, including vision, dental and domestic partners. • We encourage an atmosphere of collaboration, cooperation and collegiality. • We know that a diverse workforce with unique experiences and backgrounds makes our team stronger.