Data Engineer

MedReview; New York (NY); On-site; USD 105,000 - 115,000; Full time

Job summary

MedReview is seeking a Data Engineer to enhance our data infrastructure. This role involves designing end-to-end data pipelines on Azure, optimizing ClickHouse, and ensuring compliance with healthcare standards.

The ideal candidate will have extensive experience in data engineering, a strong proficiency in Python and SQL, and knowledge of healthcare data formats. A salary range of $105,000 to $115,000 is offered for this position.

Qualifications

• 5+ years of experience in data engineering with proficiency in Azure.
• Proven experience managing ClickHouse for large datasets.
• Expert-level skills in Python and SQL.

Responsibilities

• Design and maintain data pipelines on Azure.
• Optimize ClickHouse for large-scale datasets.
• Support ML lifecycle from feature engineering to model inference.

Skills

Cloud Expertise (Azure Data Factory, Azure Databricks)

OLAP Mastery (ClickHouse)

Python

SQL

ML Engineering (PyTorch, TensorFlow)

Healthcare Domain Knowledge

Tools

Azure Data Factory

Terraform

Kafka

Job description

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.

Salary

105,000 - 115,000