8+ years of hands-on experience in data engineering, software engineering, or cloud cost analytics
Expertise in SQL, Python, and distributed data systems (e.g., Spark, Hadoop)
Experience with cloud infrastructure (AWS, Azure, or GCP) and cost management tools
Strong communication skills to translate complex data into actionable insights for both technical and non-technical stakeholders
Requirements:
Design, build, and optimize large-scale data pipelines and architectures to automate cost attribution across compute, storage, and cloud services
Debug and resolve cost allocation issues, implementing and refining attribution logic for improved accuracy and flexibility
Create intuitive dashboards and visualizations (e.g., in Databricks, Tableau, or similar) to provide clear cost insights for engineering, finance, and leadership teams
Build scalable, reliable, and efficient datasets and pipelines, reducing manual processes through automation
Job description
Job Summary: We are seeking an experienced Data Engineer/Software Engineer to join our Multi-Cloud Efficiency (MCE) team. In this role, you will play a critical part in scaling cost attribution infrastructure and enhancing financial visibility across our cloud platforms. Your work will directly support internal stakeholders, including Technical Program Managers (TPMs), Finance, and Infrastructure teams, by delivering high-impact engineering solutions that drive cost optimization and operational efficiency. Key Responsibilities:
Design, build, and optimize large-scale data pipelines and architectures to automate cost attribution across compute, storage, and cloud services.
Debug and resolve cost allocation issues, implementing and refining attribution logic for improved accuracy and flexibility.
Develop data validation mechanisms to detect anomalies and regressions in cost and efficiency datasets.
Build scalable, reliable, and efficient datasets and pipelines, reducing manual processes through automation.
Create intuitive dashboards and visualizations (e.g., in Databricks, Tableau, or similar) to provide clear cost insights for engineering, finance, and leadership teams.
Collaborate with cross-functional teams (Executive, Product, Data, Design) to understand data infrastructure needs and resolve technical challenges.
Contribute to internal tooling and automation to minimize operational overhead and improve efficiency.
Work in a highly technical, supportive team on well-scoped problems with immediate business impact.
Stay flexible and proactive, stepping in to address critical business needs as they arise.
Required Skills & Qualifications:
8+ years of hands-on experience in data engineering, software engineering, or cloud cost analytics.
Expertise in SQL, Python, and distributed data systems (e.g., Spark, Hadoop).
Strong experience in building and optimizing data pipelines, ETL processes, and large-scale datasets.
Proficiency in debugging, root cause analysis, and problem-solving in ambiguous or operational settings.
Experience with cloud infrastructure (AWS, Azure, or GCP) and cost management tools.
Ability to translate complex data into actionable insights for both technical and non-technical stakeholders.
Strong communication skills to collaborate with finance, engineering, and leadership teams.
Preferred Qualifications:
Experience with Scala, Databricks, or similar data platforms.
Background in FinOps, cloud cost optimization, or financial data modeling.
Familiarity with data visualization tools (e.g., Tableau, Looker, Grafana).
Knowledge of Kubernetes and container cost tracking.
