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AgileEngine

AgileEngine

Data Engineering & Infrastructure Lead ID88014

Bogota, COOp locatieVastFulltime

Geplaatst 10 sep 2026

Deze baan is geplaatst in het ES

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.

Rolschets

Type baan

Fulltime

Vereiste vaardigheden

AWS container services (ECS/Fargate, ECR)Amazon RDS (Postgres)Amazon S3AWS SageMaker and MLOps pipeline designAWS EventBridgeAWS networking & CDN (VPC, ALB, CloudFront)AWS IAM (Identity and Access Management)Terraform (Infrastructure-as-Code)CI/CD pipeline design and auditingSDLC governance (schema versioning, environment separation, release gating)ETL / data-ingestion architecture (managed ELT vs custom builds)Evaluating AI-assisted / LLM-assisted development workflows (e.g., Claude Code) and cost governanceMentoring and team leadership for infrastructure/DevOps/data engineering teamsStakeholder communication and reporting to leadershipEnglish (upper-intermediate)

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