AWS Data Engineer

ABOUT THE ROLE This is a fully hands-on, individual contributor Data Engineering role embedded within a data infrastructure initiative at a large enterprise. You will own the full lifecycle of AWS-based data pipelines, from ingesting and streaming source data through to delivering clean, consumer-ready datasets for downstream use. WHAT YOU'LL DO - Stream and process source data from mainframe and legacy systems, loading it into AWS S3. - Design and implement ETL/ELT workflows using AWS Glue. - Perform data reconciliation, validation, and quality checks to ensure data accuracy and reliability. - Curate and transform data, provisioning clean datasets through AWS Aurora and RDS (PostgreSQL). - Manage S3 storage including data retention policies, archival strategies, and lifecycle management. - Automate workflows and manage deployments using GitHub and GitHub Actions-based CI/CD pipelines. - Leverage AI tools to improve engineering productivity and automate data workflows. WHAT WE'RE LOOKING FOR - 5 or more years of professional Data Engineering experience building and delivering data pipelines, ETL/ELT workflows, or data platform solutions. - Hands-on production experience with AWS Glue for designing and implementing ETL/ELT workflows. - Strong working knowledge of AWS cloud services including S3, RDS/Aurora, and Glue. - Demonstrated experience building and maintaining data streaming pipelines using Kafka. - Experience implementing data reconciliation, data quality checks, and validation processes. - Proficiency with GitHub repository management and GitHub Actions for CI/CD automation. - Experience using AI tools to automate workflows and improve productivity. - Ability to take ownership of deliverables and drive work to completion with minimal oversight. - Experience with mainframe data sources or legacy system integration is a plus. - Familiarity with MongoDB or other NoSQL databases is a plus. COMPENSATION & BENEFITS This role pays $65/hr on a W2 basis. LOCATION This role is 100% remote.