data engineer
Mercury
United States
22 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
1 year minimum
Compensation
$105,000.0 - $115,000.0
Working hours
Regular working hours
Job source
Tech stack
Query Performance
Microsoft Azure
Big Data
Computer Programming
Databases
Information Engineering
Data Infrastructure
Data Structures
Electronic Data Interchange (EDI)
Python (Programming Language)
Machine Learning
Online Analytical Processing
+25 more
Performance Tuning
Cloud Services
Tensorflow
Standard Sql
Azure Machine Learning
Data Streaming
Feature Engineering
Data Ingestion
Azure Data Factory
Pytorch
Fast Healthcare Interoperability Resources
System Availability
Kubernetes
Druid
Low Latency
Health Level Seven International
Bicep
Apache Kafka
Machine Learning Operations
Vertica
Terraform
Stream Processing
Azure Synapse Analytics
Data Pipelines
Databricks
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.
Requirements
- 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.
Benefits & conditions
Salary: 105,000 - 115,000
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