Sobre el puesto
We are looking for a Data Engineer to design build and operate the data pipelines models and platform infrastructure that power Rings analytics science and AI initiatives.
You will own the end-to-end data lifecycle - ingestion transformation modeling quality enforcement and delivery - ensuring that analysts scientists and AI systems have access to reliable well-structured data at scale.
You will use AI development IDEs and generative AI tooling daily to accelerate your work and you will build multi-agent solutions that automate common data engineering tasks - pipeline generation data quality enforcement testing and operational response.
The goal is to turn repeatable patterns into agent-driven workflows that raise velocity and consistency across the team.
You will also contribute to the shared data platform when needed - improving developer tooling maintaining infrastructure and supporting the services that the broader data org depends on.
About the team The Data and Agents Organization spans data engineering business intelligence applied science and agentic AI.
The org is structured into three primary groups one focused on core data platforms tooling and pipeline infrastructure another focused on AI/ML models business analytics shared data models product analytics and strategic science initiatives and a third focused on building a multi-agent AI platform that enables teams to compose deploy and orchestrate autonomous AI agents at scale.
Capacity is balanced across direct business support strategic new development and operational health.
BASIC QUALIFICATIONS - Experience as a data engineer or related specialty (e.g. software engineer business intelligence engineer data scientist) with a track record of manipulating processing and extracting value from large datasets - Experience in Hive/Spark/Hbase/Yarn or experience with programming/scripting (Batch VB PowerShell Java C# Chef Perl Ruby and/or PHP) and experience in any Bigdata architecture - Demonstrated use of generative AI tools (e.g. agentic coding assistants AI-powered IDEs) in a professional or project setting - Experience with software development life cycle practices including code reviews source control CI/CD testing and operational support - Experience with cloud-native data services including data warehouses object storage event streaming and serverless compute - Proficiency in Python and SQL PREFERRED QUALIFICATIONS - Experience designing or building AI agents or multi-agent solutions that automate engineering workflows - Familiarity with agentic AI patterns including tool use function calling and multi-agent orchestration - Familiarity with at least one agentic AI development IDE - Experience building or maintaining shared data models semantic layers or data contracts - Familiarity with data governance cataloging or lineage tracking - Experience contributing to shared platform infrastructure developer tooling or self-service data services - Familiarity with observability tooling for data pipelines (logging metrics alerting)