Senior Data Engineer — AWS Data Platform (Remote)

Caylent; Argentina; Presencial; ARS 134.985.151 - 194.978.552; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Annual Learning & Development stipend

Equipment & Office Stipend

Generous holidays and flexible PTO

Paid for exams and certifications

Peer bonus awards

Descripción de la vacante

Caylent is seeking a Senior Data Engineer to join a fully remote, globally distributed team. You will define RDS data sources, develop ETL jobs, and manage data warehouses on AWS for diverse clients.

Join a data-first culture that emphasizes practical impact and rigorous engineering practices. You will collaborate in cross-functional teams, participate in daily standups and biweekly agile ceremonies, and contribute to scalable solution design while advancing data engineering standards and

Formación

• 4+ years RDBMS or data engineering experience.
• 2+ years of AWS-based implementations.
• Experience with ETL and data warehousing on AWS.
• Strong knowledge of data lake/lakehouse practices.
• Hands-on experience with distributed processing (Spark/PySpark).
• Experience with streaming or event-driven ingestion patterns.
• OOP and testing in Python.

Responsabilidades

• Deliver complex data platform components or migration solutions independently
• Troubleshoot performance, scalability, and reliability issues
• Contribute to solution design and engineering standards
• Communicate technical topics clearly to peers and stakeholders
• Produce high-quality documentation and implementation reviews

Conocimientos

Cloud data platforms

Spark/PySpark

Streaming data

Python

Relational databases

Herramientas

AWS

Descripción del empleo

Caylent is seeking a Senior Data Engineer to join a fully remote, globally distributed team. You will define RDS data sources, develop ETL jobs, and manage data warehouses on AWS for diverse clients.

Join a data-first culture that emphasizes practical impact and rigorous engineering practices. You will collaborate in cross-functional teams, participate in daily standups and biweekly agile ceremonies, and contribute to scalable solution design while advancing data engineering standards and