Posted today · be early

AWS Data Engineer

Clera

WorldwideremotePosted 1 day ago

Skill Required

AWS-Data-EngineerAWS-ETL-Data-EngineerAWS-Data-EngineeringAWS-Cloud-Data-EngineeringCloud-Data-EngineerData-EngineerData EngineerAWSdata engineeringGitHub ActionsCD pipelinesEngineeringPostgreSQLautomationdesigningCOBOLbuildingEmbedded CMongoDBdesignGitKafkaCI/CDCloudETLandCICDAIFulltime

Key highlights

$65/hr (W2) compensation
5+ years of Data Engineering experience required
100% remote work
Hands‑on AWS Glue experience required
Kafka streaming pipeline experience required
Ability to work with minimal oversight

Role overview

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.

Responsibilities

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.

Requirements

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.