Description:

Fully hands-on Data Engineering role within a data infrastructure initiative at a large enterprise.
Own the full lifecycle of AWS-based data pipelines, from ingesting source data to delivering clean datasets.

Requirements:

5+ years of professional Data Engineering experience with data pipelines and ETL/ELT workflows.
Hands-on experience with AWS Glue for ETL/ELT workflows.
Strong knowledge of AWS services including S3, RDS/Aurora, and Glue.
Experience with data streaming pipelines using Kafka.
Skills in data reconciliation, validation, and quality checks.
Proficiency in GitHub and GitHub Actions for CI/CD automation.
Experience with AI tools for workflow automation.
Ability to take ownership of deliverables with minimal oversight.
Experience with mainframe data sources or legacy systems is a plus.
Familiarity with MongoDB or other NoSQL databases is a plus.

Skills