Python Engineer: Data & Gis Automation

Capgemini Engineering; Buenos Aires; Hybrid; ARS 182,771,000 - 243,694,000; Part time

Benefits offered by this job

Professional growth

Competitive USD compensation

A selection of exciting projects

Flextime

Job summary

AgileEngine is seeking a part‑time Data Engineering and Infrastructure Lead to audit AWS architecture and CI/CD processes, mentoring the team on standards. You will review SageMaker ML pipelines, tool choices, and ETL architecture while advising leadership on risk and readiness.

In this advisory role (50% to 25%), you’ll shape governance, environment separation, and release gating, ensuring scalable, cost‑efficient engineering practices for modern AI‑driven projects.

Qualifications

• 6+ years of hands‑on AWS experience with ECS/Fargate, ECR, RDS Postgres, S3, SageMaker and IAM.
• Fluency with Infrastructure‑as‑code using Terraform.
• Proven track record auditing CI/CD pipelines and SDLC governance.
• Strong data engineering depth for ETL/ingestion architecture opinions.
• Experience evaluating AI-assisted development workflows and cost governance.
• Part‑time advisory capacity (50% down to 25%) and clear mentoring ability.

Responsibilities

• Audit AWS architecture across live apps and SageMaker‑based ML pipelines.
• Review CI/CD and governance, recommending environment separation and release gates.
• Evaluate Claude Code usage for quality and cost control.
• Advise on ETL/data‑ingestion architecture between managed ELT and custom builds.
• Mentor infrastructure build team on AWS, DevOps, and data engineering best practices.
• Set directions and report findings to leadership with risk and readiness framing.

Skills

AWS

Terraform

CI/CD

SDLC governance

Data engineering

LLM tooling

Tools

SageMaker

ECS/Fargate

ECR

RDS Postgres

S3

IAM

EventBridge

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.

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.