- Clera
- Full-Time
- 30 days ago
- $65 / hour
AWS Data Engineer.
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AWS Data Engineer: our view in 3 lines...
- The Role:This role is for a data engineer building AWS-based data pipelines for a large healthcare data platform.
- The Person:The person will build and maintain AWS-based data pipelines, process and validate mainframe source data, provision clean datasets in PostgreSQL databases, and automate deployments and workflow orchestration.
- Requirements:The ideal candidate has 5+ years of Data Engineering experience, hands-on production experience with AWS services including S3, Glue, and RDS/Aurora, and proven experience building real-time data streaming pipelines using Kafka.
About the 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
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Stream and process mainframe source data into AWS S3, handling ingestion, reconciliation, and validation workflows.
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Design and implement ETL/ELT pipelines using AWS Glue to curate and transform raw data into reliable, queryable datasets.
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Provision clean, consumer-ready data through AWS Aurora/RDS PostgreSQL relational databases.
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Manage S3 storage including data retention policies, archival strategies, and lifecycle management.
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Automate deployments and orchestrate workflows using GitHub Actions and CI/CD pipelines.
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Leverage AI tools to improve engineering productivity and automate data workflow processes.
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Take ownership of deliverables and drive work to completion with minimal oversight.
What We're Looking For
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5+ years of professional Data Engineering experience delivering data pipelines, ETL/ELT workflows, or data platform solutions.
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Hands-on production experience with AWS services including S3, Glue, and RDS/Aurora.
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Proven experience building and maintaining real-time data streaming pipelines using Kafka.
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Strong background in data reconciliation, data quality checks, and validation processes.
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Experience with AWS RDS or Aurora PostgreSQL for data provisioning and querying.
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Proficiency with GitHub repository management and GitHub Actions for CI/CD automation.
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Experience using AI tools to automate workflows and boost productivity.
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Experience with MongoDB or other NoSQL databases is a plus.
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Familiarity with mainframe or legacy system data integration is a plus, but not required.
Compensation & Benefits
$65/hr (W2)
Location
Fully remote (US).
