AWS Data Engineer

Workplace
Remote
Compensation
$65 – $500k

About this role

Client: CVS Health

Job: Data Engineer

Location: 100% remote
Bill Rate/Salary: 65/Hr w2
Reason for Opening/ Day-to-day: This is a 100% hands-on individual contributor role focused on AWS-based data engineering. The engineer will help stream and process mainframe source data (mainframe skillset is not required), load it into S3, perform reconciliation and validation activities, curate and transform data, and provision clean consumer-ready datasets through AWS Aurora/RDS database. The role will also need to know automating workflows and do deployments using GitHub and CI/CD pipelines.

Key Requirements

· 5+ years of Data Engineering experience
· Must collaborate effectively with the team, take ownership of deliverables, and drive work through completion with minimal oversight.
· Hands-on AWS cloud experience
· Data streaming expertise in Kafka
· ETL/ELT experience - AWS Glue
· Data reconciliation, data quality, and data curation experience
· Experience with AWS S3 storage including data retention-archival and relational databases - such as AWS RDS/Aurora PostgreSQL
· GitHub repository management and GitHub Actions-based CI/CD
· Experience leveraging AI tools to improve productivity and automate data workflows
· Experience with MongoDB or other NoSQL databases is preferred, but not required

What happens next

Skip the application pile. I get you in front of the people who decide.

Confirm the fit

A few questions to make sure this role is the right shape for you. Two minutes.

I pitch you to the company

I write the intro, send it to the founder, and handle the back-and-forth.

A meeting lands on your calendar

When the company wants to meet, I get the call on your calendar. You just show up.

Culture & values

Work in close collaboration with Customer Success, Product and Engineering teams

Dive deep with internal and external clients to understand their needs and translate them into product improvements

Help design new offerings in the analytical space through cross-functional collaboration

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