‹ Back
Job details
Position Summary: MedReview Innovation and Development team is seeking a data engineer to function as the primary architect and operator of our data infrastructure. Y
our 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.
our 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.
Discover the company
Explore other offers from this company or learn more about MedReview Inc..
The company
M
MedReview Inc. United States
