AWS Data Engineer

About this role

ABOUT THE ROLE

This is a fully hands-on, individual contributor Data Engineering role embedded within a large-scale healthcare data platform initiative. You'll be responsible for building and maintaining AWS-based data pipelines that ingest mainframe source data, process and validate it, and deliver clean, consumer-ready datasets — work that directly supports critical downstream analytics and operations.

WHAT YOU'LL DO

- Stream and process mainframe source data into AWS S3, handling ingestion, reconciliation, and validation workflows.

- Design and implement ETL/ELT pipelines using AWS Glue to curate and transform raw data into reliable, queryable datasets.

- Provision clean, consumer-ready data through AWS Aurora/RDS PostgreSQL relational databases.

- Manage S3 storage including data retention policies, archival strategies, and lifecycle management.

- Automate deployments and orchestrate workflows using GitHub Actions and CI/CD pipelines.

- Leverage AI tools to improve engineering productivity and automate data workflow processes.

- Take ownership of deliverables and drive work to completion with minimal oversight.

WHAT WE'RE LOOKING FOR

- 5+ years of professional Data Engineering experience delivering data pipelines, ETL/ELT workflows, or data platform solutions.

- Hands-on production experience with AWS services including S3, Glue, and RDS/Aurora.

- Proven experience building and maintaining real-time data streaming pipelines using Kafka.

- Strong background in data reconciliation, data quality checks, and validation processes.

- Experience with AWS RDS or Aurora PostgreSQL for data provisioning and querying.

- Proficiency with GitHub repository management and GitHub Actions for CI/CD automation.

- Experience using AI tools to automate workflows and boost productivity.

- Experience with MongoDB or other NoSQL databases is a plus.

- Familiarity with mainframe or legacy system data integration is a plus, but not required.

COMPENSATION & BENEFITS

$65/hr (W2)

LOCATION

Fully remote (US).

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