Part-Time Data Engineering & Infra Lead (AWS/MLOps)

Félix

Rosario

Remote

ARS 182,310,000 - 243,080,000

Part time

8 days ago
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Benefits offered by this job

Professional growth
Competitive USD-based compensation
Exciting projects with Fortune 500 and
Flextime

Job summary

AgileEngine is seeking a part-time Data Engineering and Infrastructure Lead to audit AWS architecture, CI/CD processes, and ETL decisions as an advisor. You will review SageMaker-based MLOps pipelines, mentor the team on engineering standards, and weigh managed tooling vs custom builds to optimize data workflows.

The role emphasizes evaluating AI-assisted development workflows for quality and cost governance while supporting leadership with risk and readiness insights.

Qualifications

  • 6+ years of hands-on AWS experience (ECS/Fargate, ECR, RDS, S3, SageMaker).
  • Proven ability to design or audit CI/CD pipelines and SDLC governance.
  • Strong data engineering depth for ETL/ingestion architecture.
  • Comfortable mentoring engineers in a part-time advisory capacity.

Responsibilities

  • Audit AWS architecture across live apps and SageMaker-based MLOps pipelines.
  • Review CI/CD lifecycle and recommend SDLC governance layers.
  • Evaluate Claude Code usage for engineering-quality and cost governance.
  • Provide early opinions on ETL/data-ingestion architecture (ELT tooling vs custom builds).
  • Mentor the build team on AWS, DevOps, CI/CD, and data practices.
  • Propose changes and direction based on audit findings to leadership.

Skills

AWS architecture
CI/CD governance
Data engineering depth
Mentoring / coaching
English communication
LLM/AI-assisted development

Tools

Terraform

Job description

AgileEngine is seeking a part-time Data Engineering and Infrastructure Lead to audit AWS architecture, CI/CD processes, and ETL decisions as an advisor. You will review SageMaker-based MLOps pipelines, mentor the team on engineering standards, and weigh managed tooling vs custom builds to optimize data workflows.

The role emphasizes evaluating AI-assisted development workflows for quality and cost governance while supporting leadership with risk and readiness insights.

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