[Hiring] Senior Data Engineer, Cloud Economics @In All Media

Role Description

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.

Qualifications

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

Nice-to-Have Skills

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

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.