AWS Data Engineer - Lakehouse & Time-Series ETL

On.Energy; Buenos Aires; Presencial; ARS 181.190.000 - 271.784.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Medical, dental, and vision insurance

401(k) with company match

Paid time off and holidays

Descripción de la vacante

ON.energy is building the power infrastructure that enables the AI era. You’ll join a growing data team as the fourth engineer, scaling our AWS-based data lakehouse and handling high-volume time-series data from industrial sources to deliver analytics-ready datasets to end users.

No prior energy-domain experience is required; we’ll support you as you learn the domain while implementing robust ETL/ELT pipelines, governance, and scalable workflows using Apache Iceberg, Glue, Athena, Lambda, and S3.

Formación

• Bachelor’s degree in Computer Science, Computer Engineering, or closely related discipline.
• 3+ years of hands-on Data Engineering on AWS, with real exposure to modern data lakehouse architectures.
• English at B2 or above; daily collaboration with English-speaking teams and documentation.
• Experience with open table formats, preferably Apache Iceberg, and transitioning from Delta Lake or Hudi is supported.

Responsabilidades

• Build and maintain scalable ETL/ELT pipelines for batch and real-time processing.
• Evolve the Data Lakehouse with optimized storage, performance, and data consistency.
• Manage orchestration workflows with complex dependencies and error handling.
• Deliver production-ready, analytics-ready datasets and engage with end users to understand data consumption.
• Implement data governance, security controls, and audit policies across AWS.

Educación

Bachelor’s degree in Computer Science, Computer Engineering, or closely related discipline

Herramientas

Apache Iceberg

AWS Glue

AWS Athena

AWS Lambda

AWS S3

Terraform

CloudFormation

Descripción del empleo

ON.energy is building the power infrastructure that enables the AI era. You’ll join a growing data team as the fourth engineer, scaling our AWS-based data lakehouse and handling high-volume time-series data from industrial sources to deliver analytics-ready datasets to end users.

No prior energy-domain experience is required; we’ll support you as you learn the domain while implementing robust ETL/ELT pipelines, governance, and scalable workflows using Apache Iceberg, Glue, Athena, Lambda, and S3.