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
- Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
- Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
- Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
- Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
- Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
- Well-being & support: access local well-being programs and people-focused support tailored to your location
Job Type: Full-time
Work Location: Remote