Senior Platform Data Engineer

🕒 Abril 16

🔔 Pennsylvania – Remoto

🔔 Pennsylvania – Remote

⏰ Tempo Integral

🟠 Sênior

🚰 Engenheiro de Dados

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Geisinger

SiteLinkedInTodas as Vagas

10.000+ funcionários

Fundada em 1915

💊 Farmacêutico

🧘 Bem-estar

Healthcare • Pharmaceuticals • Wellness

Geisinger é uma organização de saúde que atende comunidades na Pensilvânia há mais de um século, oferecendo serviços médicos essenciais e soluções inovadoras em saúde. A organização enfatiza a diversidade, o desenvolvimento de carreira e a criação de um ambiente de apoio para seus funcionários, enquanto se esforça para melhorar a saúde e o bem-estar de seus pacientes por meio de diversos programas e iniciativas comunitárias. Geisinger é reconhecida como um dos sistemas de saúde mais inovadores e está comprometida em moldar o futuro da saúde com foco no cuidado ao paciente e na inclusividade.

Descrição

• 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.

🎯 Requisitos

• 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.

🏖️ Benefícios

• 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.