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.

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📌 Data engineering & infrastructure lead id88014 (León)
🏢 Agileengine
📍 León