Data Engineer (Healthcare)

TL;DR

Data Engineer (Azure/ClickHouse): Evolve data infrastructure into a rapid-acquisition engine for real-time ML models, innovation, and healthcare operations with an accent on pipeline architecture, high-performance storage, and compliance. Focus on designing scalable frameworks for diverse data ingestion, optimizing query performance for massive datasets, and integrating MLOps for model lifecycle management.

Salary: $105,000 - $115,000

Company

hirify.global is building innovative data platforms for healthcare claims processing, analytics, and ML-driven insights while ensuring HITRUST/HIPAA compliance.

What you will do

• Design, implement, and maintain end-to-end data pipelines on Azure for high availability and low latency in healthcare claim processing.
• Manage and optimize ClickHouse for rapid data ingestion and fast queries on large-scale datasets.
• Structure data environments to support full ML lifecycle, including feature engineering, training, and real-time inference.
• Collaborate with Data Scientists on automated CI/CD pipelines for model deployment, monitoring, and retraining.
• Develop scalable frameworks to ingest diverse healthcare data sources like EDI, claims, and clinical notes.
• Ensure all data processes adhere to HITRUST/HIPAA standards and support certification readiness.

Requirements

• 5+ years in data engineering with deep proficiency in Azure Data Factory, Azure Databricks, or Azure Synapse.
• Proven experience managing and tuning ClickHouse (or similar like Druid/Pinot) for massive datasets.
• Expert-level Python and SQL skills.
• Familiarity with ML frameworks (PyTorch, TensorFlow) and MLOps tools (MLflow, Kubeflow, Azure Machine Learning).
• Prior experience with healthcare data formats (HL7, FHIR, 835/837) and HITRUST/HIPAA security requirements.
• Ability to build initial processes designed for 10x growth.

Nice to have

• Experience with Infrastructure as Code (Terraform, Bicep).
• Knowledge of stream processing (Kafka, Azure Event Hubs).
• Background in financial or payment integrity analytics.