Data Engineering & Infrastructure Lead Id88014

AgileEngine

São Paulo

On-site

BRL 614,000 - 922,000

Part time

14 days+
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Benefits offered by this job

Professional growth
Competitive USD compensation
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 decisions in an advisory capacity. You will review SageMaker-based MLOps pipelines, mentor the team on engineering standards, and evaluate AI-assisted development workflows.

You will focus on AWS, DevOps, CI/CD, and data engineering practices, framing recommendations for technical direction and risk to leadership.

Qualifications

  • 6+ years of hands-on AWS experience: 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.
  • Strong data engineering depth for ETL / ingestion architecture.
  • Experience evaluating AI-assisted development workflows (Claude Code) for governance and cost.
  • Part-time advisory capacity (50% down to 25%).
  • Upper-intermediate English level.

Responsibilities

  • Audit AWS architecture across live applications (ECS/ECR, RDS, S3, VPC, CloudFront, SageMaker).
  • Review CI/CD process and SDLC governance, recommending changes.
  • Evaluate use of Claude Code for code generation and reviews.
  • Advise on ETL/data-ingestion architecture (managed vs custom).
  • Mentor infrastructure build team focusing on AWS, DevOps, and data practices.
  • Provide recommendations and set technical direction from audit findings.
  • Report findings to leadership with risk and readiness assessments.

Skills

AWS expertise
Terraform
CI/CD pipelines
SDLC governance
ETL / data engineering
Mentoring
English (upper-intermediate)

Tools

SageMaker
Claude Code
ECS/Fargate
RDS

Job description

Job Description

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.
  • Upper-intermediate English level.
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.
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