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Clera

AWS Data Engineer

remote (Remote)$135.2k–$135.2kfulltimemidAdded today

About this role

Build and maintain AWS-based data pipelines for a healthcare platform, ingesting mainframe data into S3, transforming it with Glue, and delivering validated datasets through PostgreSQL databases. This is a hands-on individual contributor role requiring 5+ years of data engineering experience with strong AWS and Kafka expertise.

What you'll do

  • Stream and process mainframe source data into AWS S3 with ingestion, reconciliation, and validation workflows
  • Design and implement ETL/ELT pipelines using AWS Glue to transform raw data into queryable datasets
  • Provision clean data through AWS Aurora/RDS PostgreSQL relational databases
  • Manage S3 storage including 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 processes

What they're looking for

  • AWS (S3, Glue, RDS, Aurora)
  • ETL/ELT pipeline design and implementation
  • Apache Kafka for real-time data streaming
  • PostgreSQL and relational databases
  • Data reconciliation and quality validation
  • GitHub and GitHub Actions
  • Python or Java for data engineering
  • AI tools for workflow automation

Benefits

  • Fully remote position (US-based)
  • Work on critical healthcare data platform initiative
  • Hands-on technical role with minimal oversight required
  • Opportunity to use AI tools to boost productivity
  • Exposure to large-scale data engineering challenges
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Clera

Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.

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Likely interview questions

  • Describe your experience building Kafka-based real-time streaming pipelines in production—what were the key challenges?
  • Walk us through how you've designed and implemented data validation and reconciliation workflows in a previous role.
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