Remote Lead Aws Data Engineer — Migrations & Architecture

Perficient

Ciudad de Mendoza

Remote

ARS 136,310,000 - 212,038,000

Part time

3 days ago
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Benefits offered by this job

Professional growth
Competitive USD-based compensation
A selection of exciting projects
Flextime

Job summary

AgileEngine is seeking a part-time Data Engineering and Infrastructure Lead to audit AWS architecture, CI/CD processes, and ETL pipeline decisions in an advisory capacity. This role weighs managed tooling against custom builds, reviews SageMaker-based MLOps pipelines, and mentors the team on engineering standards.

Evaluating AI-assisted development workflows is part of the role. You will mentor and accelerate the day-to-day infrastructure build team, focusing on AWS, DevOps, CI/CD, and data

Qualifications

  • 6+ years of hands-on AWS experience (ECS/Fargate, ECR, RDS, S3, SageMaker, EventBridge, VPC/ALB/CloudFront, IAM).
  • TerraformIA C/O infrastructure-as-code proficiency.
  • Proven track record designing/auditing CI/CD pipelines and SDLC governance.
  • Strong data engineering depth for ETL/ingestion architecture opinions.
  • Experience evaluating AI-assisted (LLM) development workflows.
  • Part-time advisory capacity (50% to 25%).
  • Upper-intermediate English level.

Responsibilities

  • Audit current AWS architecture across live apps; assess CI/CD lifecycle.
  • Review SDLC governance: schema/versioning, environment separation, release gating.
  • Evaluate Claude Code usage for engineering-quality and cost governance.
  • Provide early technical opinions on ETL/data-ingestion architecture (managed vs. custom).
  • Mentor infrastructure build team in AWS, DevOps, CI/CD, data engineering.
  • Set out recommendations and direction from audit findings to leadership.
  • Report findings and recommendations with risk and readiness.

Skills

Upper-intermediate English
Cloud advisory
Strong communication

Tools

AWS (ECS/Fargate)
SageMaker
Terraform
CI/CD
Claude Code

Job description

Data Engineering & Infrastructure Lead ID88014

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE

We are looking for a part-time Data Engineering and Infrastructure Lead to audit AWS architecture, CI/CD processes, and ETL pipeline decisions in an advisory capacity. This person weighs managed tooling against custom builds, reviews SageMaker-based MLOps pipelines, and mentors the team on engineering standards. Evaluating AI-assisted development workflows is part of the role.

WHAT YOU WILL DO
  • Audit the current AWS architecture across live applications (MAT / Signal IQ and the Impact Engine), including ECS/ECR, RDS (Postgres), S3, VPC, CloudFront/SSO, and SageMaker-based MLOps pipeline design.
  • Review the CI/CD process and end-to-end app development lifecycle, recommending SDLC governance layers (schema versioning, environment separation, release gating).
  • Evaluate how the team uses Claude Code (PR generation, automated reviews, token/cost management) to confirm output meets professional engineering standards.
  • Provide an early technical opinion on ETL / data-ingestion pipeline architecture (managed ELT tooling vs. custom build).
  • Mentor and accelerate the day-to-day infrastructure build team, focusing on AWS, DevOps, CI/CD, and data engineering practices.
  • Set out recommendations and technical direction where the audit surfaces necessary changes to the current build.
  • Report findings and recommendations directly to leadership, framing high-level risk and readiness.
MUST HAVES
  • 6+ years of deep, current hands-on experience with AWS: ECS/Fargate, ECR, RDS (Postgres), S3, SageMaker, EventBridge, VPC/ALB/CloudFront, IAM.
  • Fluency in Infrastructure-as-code, specifically Terraform.
  • Proven track record designing or auditing CI/CD pipelines and SDLC governance (e.g., Alembic for schema/version control, environment separation, release gating).
  • Strong data engineering depth to provide defensible opinions on ETL / ingestion architecture (managed tools vs. custom builds).
  • Experience evaluating AI-assisted / LLM-assisted development workflows (e.g., Claude Code) from an engineering-quality and cost-governance standpoint.
  • Comfortable operating in a part-time advisory capacity (50% stepping down to 25%) as a strong communicator who can mentor less experienced engineers.
NICE TO HAVES
  • Prior experience working with small, fast-moving engineering teams.
  • Understanding of MLOps pipelines and data science infrastructure.
  • Media/AdTech domain knowledge is helpful but not required.
PERKS AND BENEFITS
  • Professional growth : Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.
  • Competitive compensation : We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.
  • A selection of exciting projects : Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.
  • Flextime : Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office - whatever makes you the happiest and most productive.
Requirements
  • 6+ years of deep, current hands-on experience with AWS: ECS/Fargate, ECR, RDS (Postgres), S3, SageMaker, EventBridge, VPC/ALB/CloudFront, IAM.
  • Fluency in Infrastructure-as-code, specifically Terraform.
  • Proven track record designing or auditing CI/CD pipelines and SDLC governance (e.g., Alembic for schema/version control, environment separation, release gating).
  • Strong data engineering depth to provide defensible opinions on ETL / ingestion architecture (managed tools vs. custom builds).
  • Experience evaluating AI-assisted / LLM-assisted development workflows (e.g., Claude Code) from an engineering-quality and cost-governance standpoint.
  • Comfortable operating in a part-time advisory capacity (50% stepping down to 25%) as a strong communicator who can mentor less experienced engineers.
  • Upper-intermediate English level.
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