Description:

Fully hands-on Data Engineering role within a large-scale healthcare data platform initiative.
Responsible for building and maintaining AWS-based data pipelines for mainframe source data processing and validation.

Requirements:

5+ years of professional Data Engineering experience with data pipelines and ETL/ELT workflows.
Hands-on experience with AWS services including S3, Glue, and RDS/Aurora.
Proven experience with real-time data streaming pipelines using Kafka.
Strong background in data reconciliation, quality checks, and validation processes.
Experience with AWS RDS or Aurora PostgreSQL.
Proficiency in GitHub repository management and CI/CD automation using GitHub Actions.
Experience with AI tools for workflow automation is preferred.
Familiarity with MongoDB or NoSQL databases is a plus.
Knowledge of mainframe or legacy system data integration is a plus but not required.

Skills