AWS Data Engineer — Real-Time Lakehouse for AI Energy

ON.energy; Municipio de Esquel; On-site; ARS 90,952,000 - 136,428,000; Full time

Job summary

ON.energy is building the data backbone for its AI-driven power infrastructure, and you will join as a Data Engineer on AWS lakehouse workloads.

You’ll design and operate ETL/ELT pipelines, manage orchestration, enforce governance, and work with high-volume time-series data from industrial sources, collaborating with English-speaking teams.

No prior energy domain experience is required, and we’ll support your learning as you grow with the team.

Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, or a related field.
• 3+ years of hands-on Data Engineering on AWS with data lakehouse experience.
• English at B2 or above; daily use with English-speaking teams.
• Experience with open table formats, preferably Apache Iceberg.
• Core AWS data services: Glue, Athena, Lambda, and S3.
• Proficient in Python (PySpark) and advanced SQL.
• Data modeling for analytical workloads in lakehouse architectures.
• Infrastructure as Code: Terraform or CloudFormation.

Responsibilities

• Build and maintain scalable ETL/ELT pipelines for batch and real-time processing.
• Evolve the Data Lakehouse, optimizing storage, performance, and cost.
• Manage orchestration workflows with complex dependencies and error handling.
• Deliver production-ready, analytics-optimized datasets for end users.
• Implement data governance, security controls, and audits across AWS.
• Build monitoring, alerting, and data quality testing for reliability.

Skills

Python

SQL

ETL/ELT pipelines

AWS

Iceberg

Terraform

CloudFormation

English (B2)

Education

Bachelor’s degree in CS/CE

Tools

Glue

Athena

Lambda

S3

Apache Iceberg

Job description

ON.energy is building the data backbone for its AI-driven power infrastructure, and you will join as a Data Engineer on AWS lakehouse workloads.

You’ll design and operate ETL/ELT pipelines, manage orchestration, enforce governance, and work with high-volume time-series data from industrial sources, collaborating with English-speaking teams.

No prior energy domain experience is required, and we’ll support your learning as you grow with the team.