Data Engineering & Infrastructure Lead Id88014 (Villavicencio)

Data Engineering & Infrastructure Lead Id88014 (Villavicencio)

15 oct
|
Agileengine
|
Villavicencio

15 oct

Agileengine

Villavicencio

Agile

Engine 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 ROLEWe 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 Sage

Maker-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, Cloud

Front/SSO, and Sage

Maker-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, Dev

Ops, 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, Sage

Maker, Event

Bridge, VPC/ALB/Cloud

Front, 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, Tech

Talks, 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, Sage

Maker, Event

Bridge, VPC/ALB/Cloud

Front, 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.#J-18808-Ljbffr

📌 Data Engineering & Infrastructure Lead Id88014 (Villavicencio)
🏢 Agileengine
📍 Villavicencio

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