Remote Senior Data Engineer - Build Cost Driven Pipelines

Encora Inc.; Ciudad de Mendoza; Hybrid; ARS 90,873,000 - 166,601,000; Full time

Benefits offered by this job

Professional growth

Competitive USD-based compensation

Projects with Fortune 500 brands

Flextime: work from home or office

Job summary

AgileEngine is hiring a Data Engineer to build data pipelines and tooling for cost attribution, optimization, and financial modeling. You will enable product, engineering, analytics, and finance stakeholders to make data‑driven decisions and trust the data.

You will develop pipelines to surface cost transparency and support discounted usage modeling, while maintaining end‑to‑end ELT/ETL data flows, data modeling, and schema maturity.

Qualifications

• 4+ years of data engineering experience.
• Hands-on with SQL, Python, Spark, and Scala.
• Hands-on with workflow tools: dbt, Airflow, Dagster.
• Experience with AWS (Glue, Aurora, Athena), GCP and Snowflake.
• Experience architecting ELT/ETL data pipelines, modeling, and schema maturity.
• Exposure to CI/CD, Infrastructure as Code (Terraform), and REST APIs.
• Strong attention to detail, analytical skills, and data auditing.
• Ability to explain technical concepts to non-technical audiences.

Responsibilities

• Develop and implement tooling and datasets for telemetry-driven cost attribution and financial modeling.
• Build and maintain data pipelines that provide cost transparency and surface optimization opportunities.

Skills

SQL

Python

Spark

Scala

REST API

CI/CD

Data auditing

Explain concepts

Tools

dbt

Airflow

Dagster

AWS

Glue

Aurora

Athena

GCP

Snowflake

Terraform

Job description

AgileEngine is hiring a Data Engineer to build data pipelines and tooling for cost attribution, optimization, and financial modeling. You will enable product, engineering, analytics, and finance stakeholders to make data‑driven decisions and trust the data.

You will develop pipelines to surface cost transparency and support discounted usage modeling, while maintaining end‑to‑end ELT/ETL data flows, data modeling, and schema maturity.