Remote Data Engineer

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.