Caylent is a cloud native services company that helps organizations bring the best out of their people and technology using Amazon Web Services (AWS). We provide a full-range of AWS services including workload migrations and modernization, cloud native application development, DevOps, data engineering, security and compliance, and everything in between.
We are a global company and operate fully remote with employees in Canada, the United States, and Latin America. Come talk to us to learn more about what it means to be a Caylien The Mission At Caylent, a Senior Data Engineer is an integral part of a cross-functional delivery team implementing data management solutions on AWS for our customers. You will work in a hands-on capacity to define RDS data sources, develop ETL jobs, and manage data warehouses. You will participate in daily standups with your team and in biweekly agile ceremonies with the customer. Deliver complex data platform components or migration solutions independently
Troubleshoot performance, scalability, and reliability issues
Contribute to solution design and engineering standards
Produce high-quality documentation and implementation reviews
Strong experience building scalable cloud-native data platforms and pipelines
Advanced knowledge of modern data lake/lakehouse practices
Hands-on experience with distributed processing (Spark/PySpark or equivalent)
Python with solid engineering principles (OOP, testing)
Strong expertise in relational databases and schema design
Advanced query optimization and performance troubleshooting
Cloud security fundamentals
4+ years RDBMS or data engineering experience.
2+ years of AWS-based implementations.
Upper-Intermediate English (minimum B2).
100% remote work
Generous holidays and versátil PTO
Equipment & Office Stipend
Individual professional development plan
NOTE: We're unable to provide visa sponsorship now or at any time in the future.
If an AI or automated tool is used during your application process, it will
📌 Senior Data Engineer (Mérida)
🏢 Caylent
📍 Mérida
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