Data Engineer

MedReview Inc.; New York (NY); On-site; USD 120,000 - 150,000; Full time

Job summary

A healthcare technology company is seeking a Data Engineer to architect and manage data infrastructure. You will design Azure data pipelines, manage ClickHouse for analytics, and ensure compliance with healthcare standards like HITRUST/HIPAA. The ideal candidate should have over 5 years of data engineering experience with strong skills in Python and SQL, and familiarity with healthcare data formats. This role offers an opportunity to enable rapid data acquisition and support ML operations.

Qualifications

• 5+ years of experience in data engineering, particularly with cloud platforms.
• Strong programming skills in Python and SQL.
• Experience managing and tuning columnar databases for large datasets.

Responsibilities

• Design and maintain data pipelines on Azure for healthcare processing.
• Manage ClickHouse for rapid data ingestion and querying.
• Implement CI/CD pipelines for ML model deployment and monitoring.

Skills

Data engineering

Azure Data Factory

Python

SQL

Healthcare data formats

MLOps

Tools

ClickHouse

Azure Databricks

Azure Synapse

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 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.