Remote Data Engineer for Cost Attribution & Pipelines

Encora Inc.; Ciudad de Mendoza; Remote; ARS 138.361.000 - 230.602.000; Vollzeit

Benefits dieser Stelle

Professional growth

Competitive USD-based compensation

A selection of exciting projects

Flextime

Zusammenfassung

AgileEngine in Mendoza is seeking a Data Engineer to build data pipelines and tooling for cost attribution, optimization, and financial modeling. You will enable stakeholders to make data-driven decisions with trust in the data.

You will work with SQL, Python, Spark, Scala, and modern orchestration and cloud tools, shaping end-to-end ELT/ETL pipelines and promoting maintainability and accuracy across finance and product teams.

Qualifikationen

• 4+ years in Data Engineering roles.
• Hands-on with SQL, Python, Spark, and Scala.
• Hands-on with workflow orchestration tools such as dbt, Airflow, and Dagster.
• Hands-on experience with AWS (Glue, Aurora, Athena), GCP, and Snowflake.
• Experience architecting end-to-end ELT/ETL data pipelines with data modeling.
• Exposure to CI/CD, Infrastructure as Code (Terraform), and REST API programming.
• Strong attention to detail, analytics and data auditing skills.
• Ability to explain technical concepts to non-technical audiences.

Aufgaben

• Develop and implement tooling and datasets for cost attribution and financial modeling.
• Build and maintain data pipelines providing cost transparency and surface optimization opportunities.
• Collaborate with product, engineering, analyst, and finance stakeholders to enable data-driven decisions.

Kenntnisse

SQL

Python

Spark

Scala

dbt

Airflow

Dagster

AWS

GCP

Snowflake

ELT/ETL

CI/CD

Terraform

REST APIs

Tools

Go

Jobbeschreibung

AgileEngine in Mendoza is seeking a Data Engineer to build data pipelines and tooling for cost attribution, optimization, and financial modeling. You will enable stakeholders to make data-driven decisions with trust in the data.

You will work with SQL, Python, Spark, Scala, and modern orchestration and cloud tools, shaping end-to-end ELT/ETL pipelines and promoting maintainability and accuracy across finance and product teams.