Clera
via Ashby
AWS Data Engineer
This is the employer's own posting, not a copy on a job board.
What we know
Is it still open?
Confirmed still open
Last checked 20h ago — checked against the employer's own applicant tracking system, which is the company answering directly.
We re-read the employer's own applicant tracking system and the posting was still there. That is the company answering directly.
How old is it?
Posted 22h ago
The date the source published, not the day we noticed it (2026-09-14). Last seen at its source just now.
Is it remote?
remote
That is the location the employer filed this posting under. Quoted as written — we do not re-word the source's own location.
Who may apply?
United States
No source stated where this role may be worked. This is read from the ad's own words.
What the ad says
…based anywhere in the United States are welcome…
Pay
$65–100/hr
Read out of the job description by us, not from a structured field. Shown in the posting's own currency and period; we never convert.
Skills named in the ad
Recognised terms only, from a fixed vocabulary — this is what CV matching compares against.
Carried by 1 source
-
ashby employer's own board first seen 21h ago · last seen just now
- location not stated
The listing
About the Role
This is a fully hands-on individual contributor role on a data engineering team within the healthcare industry. You will own the end-to-end movement and transformation of data, from ingesting mainframe source streams into AWS through to provisioning clean, consumer-ready datasets. Your work directly enables downstream analytics and operational systems at scale.
What You'll Do
Stream and process mainframe source data into AWS S3 using modern data pipeline tooling.
Design and implement ETL/ELT workflows using AWS Glue to curate and transform data.
Perform data reconciliation, validation, and quality checks across ingested datasets.
Provision clean, consumer-ready datasets through AWS Aurora and RDS PostgreSQL databases.
Manage S3 storage including data retention policies, archival strategies, and lifecycle management.
Automate and deploy workflows using GitHub Actions and 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 delivering data pipelines, ETL/ELT workflows, or data platform solutions.
Hands-on production experience with AWS Glue for ETL/ELT design and implementation.
Strong working knowledge of AWS S3, RDS, and Aurora in production environments.
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 boost engineering productivity.
Ability to own 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 is a W2 contract engagement. The bill rate is $65/hour.
Location
This role is 100% remote. Candidates based anywhere in the United States are welcome to apply.