1990 Senior Data Engineer, Cloud Cost & Usage Platform

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

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.

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.

• →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.

• 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.

• 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.

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.

#LI