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In All Media Inc

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1990 Senior Data Engineer, Cloud Cost & Usage Platform

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Summary

Senior Data Engineer on a Cloud FinOps project, building and maintaining ELT/ETL pipelines, data models, and tooling that turn high-volume cloud telemetry and usage data into cost visibility and spend attribution for Product, Engineering, and Finance. Core stack: SQL, Python, Snowflake, dbt/Airflow/Dagster, and the AWS data ecosystem (Glue, Athena, Aurora) with Terraform-based IaC.

📌 Position: Senior Data Engineer, Cloud Economics

Location: Remote from LATAM

Contract Type: Full-time vendor (via https://inallmedia.com/)

Time Zone Alignment: CT ±2

Experience Level: 5+ years in Data Engineering

🧭 ABOUT INALLMEDIA.COM

Inallmedia.com is a global technology and design firm focused on building impactful digital solutions through remote, distributed teams across LATAM. We partner with international clients across industries, providing long-term technical expertise, product innovation, and team augmentation.

🚀 PROJECT OVERVIEW

You will join the Cloud Economics Team to focus on engineering scalable data infrastructure capable of processing high-volume telemetry and infrastructure usage metrics.

The ultimate goal of this project is to provide granular cost visibility, accurate spend attribution, and data-driven insights. This initiative directly empowers Product, Engineering, and Finance departments to optimize cloud infrastructure costs, driving maximum efficiency and performance across the business.

This is a data platform role at its core. If you have built large-scale pipelines on AWS and want to apply that to a problem with direct, measurable business impact, you will find plenty to work on here.

🔍 KEY RESPONSIBILITIES

  • Pipeline Design & Maintenance: Design, build, and maintain the Cloud Economics team's data pipelines, automation systems, and datasets that power cloud cost visibility, attribution, and insights.
  • Data Modeling & Ingestion: Design and implement highly scalable data models and ingestion frameworks to support large-scale telemetry and usage data.
  • Tooling Development: Develop specialized tooling that enables cost-aware decision-making across Product, Engineering, and Finance stakeholders.
  • System Optimization: Optimize data systems for performance, reliability, and cost-efficiency, including query tuning, storage strategies, and compute optimization.
  • Cross-Functional Collaboration: Partner directly with Engineering and Finance teams to support cost-optimization initiatives and usage-based insights.
  • Data Governance: Ensure rigorous data quality, validation, auditing, and troubleshooting protocols across all end-to-end production data workflows.

💡 MUST-HAVE SKILLS

  • Core Engineering Foundation: Strong Data Engineering background with proven experience building and maintaining end-to-end ELT/ETL pipelines in cloud environments.
  • Programming & Databases: Strong SQL and Python skills, alongside hands-on experience with a modern cloud data warehouse (Snowflake or Databricks).
  • Orchestration Tools: Direct experience with orchestration tools such as dbt, Airflow, or Dagster.
  • AWS Ecosystem: Deep familiarity with the AWS data ecosystem, including AWS Glue, Amazon Athena, AWS Lambda, and Step Functions.
  • DevOps & Infrastructure: Solid experience with CI/CD, version control, Infrastructure as Code (IaC) via Terraform, and building REST API integrations.
  • Data Architecture: Extensive data modeling and large-scale data processing experience.
  • Language: Fluent English for daily communication.

🌟 NICE-TO-HAVE SKILLS

  • Domain Exposure: Any experience with cloud cost optimization, tagging strategies, cost monitoring, or billing data pipelines (AWS Cost and Usage Report, FOCUS, cost allocation, chargeback, showback).
  • Certifications: FinOps Foundation Certification (Practitioner or Engineer level).
  • Lakehouse & Architecture: Apache Iceberg, Delta Lake, medallion architecture, or a background in data platform or shared infrastructure engineering.
  • Languages: Proficiency in Scala is a plus.
  • Multi-Cloud & Monitoring: Familiarity with both AWS and GCP, alongside experience using Datadog.
  • Background: Academic or professional experience in Economics, Finance, or Econometrics.

✅ A NOTE ON FINOPS EXPERIENCE

We are looking for a strong data engineer first. The cloud cost domain is learnable on the job, and the team will support you in picking it up. If you have ever tuned a warehouse, optimized compute spend, or investigated an unexpected infrastructure bill, you already have useful context.

Please do not filter yourself out of this one.

🌐 TIME ZONE & COLLABORATION

The role requires collaboration with teams aligned to the Central Time (CT) zone. Candidates should be available to overlap several hours with US-based teams.

💬 LANGUAGE

All interviews, documentation, and daily communication will be conducted in English.

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