Azure & AWS Data Engineering
Budget: ₹12,500 – ₹37,500 INR
Data Engineer_ Microsoft Azure and AWS
Location: Remote
Working Time: evening
Budget: 22-24k monthly
Duration:-2 hours per day
Demo Required: Today
Job Description
We are seeking an experienced Senior Data Engineer with strong expertise in the Healthcare Payer domain to design, build, and maintain scalable data pipelines and reporting solutions. The ideal candidate will have hands-on experience across AWS and Microsoft Azure, strong Python/PySpark skills, and the ability to support integrated reporting and analytics using Power BI.
Key Responsibilities
Design, develop, and maintain end-to-end data pipelines for healthcare payer data
Build and optimize ETL/ELT workflows using AWS Glue, Step Functions, and Python
Work with Azure and AWS cloud services for data ingestion, processing, and storage
Implement and manage Data Lake architecture (structured & unstructured data)
Ensure high data quality, reliability, and performance across pipelines
Support integrated reporting and analytics use cases
Collaborate with business, analytics, and reporting teams to understand payer data requirements
Enable dashboards and reports using Power BI
Handle large-scale datasets related to claims, eligibility, providers, members, premiums, and payments
Location: Remote
Working Time: evening
Budget: 22-24k monthly
Duration:-2 hours per day
Demo Required: Today
Job Description
We are seeking an experienced Senior Data Engineer with strong expertise in the Healthcare Payer domain to design, build, and maintain scalable data pipelines and reporting solutions. The ideal candidate will have hands-on experience across AWS and Microsoft Azure, strong Python/PySpark skills, and the ability to support integrated reporting and analytics using Power BI.
Key Responsibilities
Design, develop, and maintain end-to-end data pipelines for healthcare payer data
Build and optimize ETL/ELT workflows using AWS Glue, Step Functions, and Python
Work with Azure and AWS cloud services for data ingestion, processing, and storage
Implement and manage Data Lake architecture (structured & unstructured data)
Ensure high data quality, reliability, and performance across pipelines
Support integrated reporting and analytics use cases
Collaborate with business, analytics, and reporting teams to understand payer data requirements
Enable dashboards and reports using Power BI
Handle large-scale datasets related to claims, eligibility, providers, members, premiums, and payments
Related categories:
Python
Azure
Amazon Web Services
Data Integration
Power BI
Microsoft Azure
PySpark
Data Management
Terraform
CI/CD