1990 Senior Data Engineer, Cloud Cost & Usage Platform

📌 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…