- Location
- BR
- Workplace
- Remote
- Type
- Full-time
- Department
- Engineering
- Seniority
- Senior
- Source
- Breezy HR
Description
📌 Position: Senior Data Engineer (Cloud FinOps)
Location: Remote from LATAM
Contract Type: Full-time vendor (via https://inallmedia.com/)
Time Zone Alignment: CT ±2
🧭 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.
🔍 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 direct experience with Snowflake.
- 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, and Amazon Aurora.
- 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
- Languages: Proficiency in Scala is a plus.
- Certifications: FinOps Foundation Certification (Practitioner or Engineer level).
- Domain Expertise: Experience with cloud cost optimization, tagging strategies, cost monitoring, and a background in data platform or shared infrastructure engineering.
- Multi-Cloud & Monitoring: Familiarity with both AWS and GCP, alongside experience using Datadog.
🌐 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.
