Senior Data Engineer, Marketing Analytics - Remote

Jpmorgan Chase & Co.; Rosario; Remote; ARS 107,614,000 - 169,108,000; Full time

Job summary

AgileEngine is seeking a Data Engineer to design and implement data pipelines and tooling for cost attribution, optimization, and financial modeling.

You will build datasets and pipelines to provide cost transparency and enable data-driven decisions for product, engineering, analyst, and finance stakeholders. The role emphasizes ELT/ETL, data modeling, and end-to-end validation.

Qualifications

• 4+ years of experience in Data Engineering roles.
• Hands-on with SQL, Python, Spark and Scala.
• Hands-on with workflow orchestration tools: dbt, Airflow, Dagster.
• Experience with AWS (Glue, Aurora, Athena), GCP, and Snowflake; ELT/ETL data pipelines.
• Experience with data modeling, schema maturity, and end-to-end validation.
• Exposure to CI/CD and Infrastructure as Code (Terraform), and REST API programming.
• Strong communication to explain technical concepts to non-technical audiences.

Responsibilities

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

Skills

SQL

Python

Spark

Scala

CI/CD

Data modeling

REST API

Tools

dbt

Airflow

Dagster

Terraform

AWS

GCP

Snowflake

Job description

AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE

We are looking for a Data Engineer to build data pipelines and tooling for cost attribution, optimization, and financial modeling.

WHAT YOU WILL DO

• Develop and implement tooling and datasets that drive telemetry-driven cost attribution and performance-informed financial modeling, enabling product, engineering, analyst, and finance stakeholders to make faster, data-driven decisions and trust the data.
• Build and maintain data pipelines and tooling that provide cost transparency, surface optimization opportunities, and support committed use discount modeling and management.

MUST HAVES

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

NICE TO HAVES

• Experience with FinOps teams or cost optimization job duties.
• FinOps Practitioner or FinOps Engineer certification.
• Experience with Datadog API endpoints.