Full Stack Data Engineer

Ryz Labs is looking for a Full-Stack Data Engineer who can design, build, and own modern data platforms end-to-end: from ingestion pipelines and cloud infrastructure through to high-quality, production-grade code. You’ll pair traditional data-engineering strengths with solid software-development practices to deliver resilient data products that scale. This role is perfect for someone who thrives in high-pressure environments, values straight talk, and takes deep pride in craftsmanship, even when requirements are ambiguous.
Key Responsibilities
• Design & build pipelines – Develop, test, and maintain robust batch and streaming data pipelines in Python, SQL, and Spark/Databricks.• Engineer infrastructure – Provision and evolve cloud resources (AWS, Azure, or GCP) via IaCframeworks such as Terraform or CloudFormation.• Apply software-craft disciplines – Enforce version control, automated testing, CI/CD, and codereviews; write clean, idiomatic, well-documented Python.• Author design artefacts – Produce clear architectural diagrams, ADRs, and technical designdocuments that guide implementation and onboarding.• Monitor & optimize – Instrument pipelines, build dashboards, and tune performance; own incident response and root-cause analysis.• Champion data quality & governance – Implement validation, lineage, and observability to guarantee trustworthy data assets.• Collaborate cross-functionally – Partner with product, data science, and platform teams to translate business questions into scalable data solutions.
Required Skills & Qualifications
Certifications• Databricks certified data engineers• Cloud specific data engineering certifications
Technical Expertise• Python mastery – OOP, type hints, packaging, and performance tuning.• Spark mastery - Performance tuning and data engineering optimizations• SQL mastery - Expert SQL and data-model design for relational databases.• Infrastructure-as-Code (Terraform, CDK, or ARM) and CI/CD tooling (GitHub Actions, Jenkins, Azure DevOps).• Knowledge of observability/monitoring (Datadog, Prometheus, OpenTelemetry) for data services.• Well-versed in the setup of data quality and data integrity pipelines• Comfortable with writing design documents
About RYZ Labs:
RYZ Labs is a startup studio built in 2021 by two lifelong entrepreneurs. The founders of RYZ have worked at some of the world's largest tech companies and some of the most iconic consumer brands. They have lived and worked in Argentina for many years and have decades of experience in Latam. What brought them together is the passion for the early phases of company creation and the idea of attracting the brightest talents in order to build industry-defining companies in a post-pandemic world.
Our teams are remote and distributed throughout the US and Latam. They use the latest cutting-edge technologies in cloud computing to create applications that are scalable and resilient. We aim to provide diverse product solutions for different industries, planning to build a large number of startups in the upcoming years.
At RYZ, you will find yourself working with autonomy and efficiency, owning every step of your development. We provide an environment of opportunities, learning, growth, expansion and challenging projects. You will deepen your experience while sharing and learning from a team of great professionals and specialists.
Our values and what to expect:
- Customer First Mentality - every decision we make should be made through the lens of the customer.- Bias for Action - urgency is critical, expect that the timeline to get something done is accelerated. - Ownership -  step up if you see an opportunity to help, even if not your core responsibility. - Humility and Respect - be willing to learn, be vulnerable, and treat everyone that interacts with RYZ with respect.- Frugality - being frugal and cost-conscious helps us do more with less.- Deliver Impact - get things done in the most efficient way. - Raise our Standards - always be looking to improve our processes, our team, our expectations. Status quo is not good enough and never should be.