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Data Engineergrabjobs • United States
Postuler Maintenant
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Data Engineer

grabjobs
  • US
    United States
  • US
    United States
Postuler Maintenant

À propos

Position Summary: MedReview Innovation and Development team is seeking a data engineer to function as the primary architect and operator of our data infrastructure. Your mission is to evolve our current environment into a rapid-acquisition engine capable of feeding real-time ML models, innovation, and operations while maintaining rigorous healthcare compliance standards.
Responsibilities:
Pipeline Architecture:
Design, implement, and maintain end-to-end data pipelines on
Azure , ensuring high availability and low latency for healthcare claim and analytics processing. High-Performance Storage:
Manage and optimize
ClickHouse
as our primary analytical engine, focusing on rapid data ingestion and lightning-fast query performance for large-scale datasets. ML Data Readiness:
Structure data environments to support the full ML lifecycle, from feature engineering and training to real-time model inference. MLOps Integration:
Collaborate with Data Scientists to implement automated CI/CD pipelines for model deployment, monitoring, and retraining. Rapid Acquisition:
Develop scalable frameworks to ingest diverse healthcare data sources (EDI, claims, clinical notes) with high velocity. Security & Compliance:
Ensure all data structures and processes adhere to
HITRUST/HIPAA
standards, collaborating with IT and the leads for technical efforts for
HITRUST certification
readiness. Required Skills & Experience
Cloud Expertise:
5+ years of experience in data engineering, with deep proficiency in
Azure Data Factory, Azure Databricks, or Azure Synapse . OLAP Mastery:
Proven experience managing and tuning
ClickHouse
(or similar columnar databases like Druid/Pinot) for massive datasets. Programming:
Expert-level
Python
and
SQL
skills. ML Engineering:
Familiarity with ML frameworks (PyTorch, TensorFlow) and MLOps tools (MLflow, Kubeflow, or Azure Machine Learning). Healthcare Domain:
Prior experience with healthcare data formats (HL7, FHIR, 835/837) and a strong understanding of
HITRUST/HIPAA
security requirements. Scale-up Mindset:
Ability to build "v1" processes while designing for 10x growth. Preferred Qualifications:
Experience with Infrastructure as Code (Terraform, Bicep). Knowledge of stream processing (Kafka, Azure Event Hubs). Background in financial or payment integrity analytics.
  • United States

Compétences linguistiques

  • English
Avis aux utilisateurs

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