Podcast
FinOps for Data Engineers: Optimize Cloud Costs, BigQuery & Modern Data Stack
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FinOps for Data Engineers: Optimize Cloud Costs, BigQuery & Modern Data Stack
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Episode Overview
How can data engineers bring FinOps practices into their day-to-day work to control cloud spend across BigQuery and the modern data stack? In this episode, Eddy Zulkifly — Staff Data Engineer at Kinaxis with a decade of experience building data platforms on Google Cloud, Azure, and AWS — breaks down practical ways to make cost optimization part of platform design and operations.
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Chapter Summary
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- 0:00 - Podcast Introduction
- 1:35 - Guest Introduction: Eddy Zulkifly, Staff Data Engineer at Kinaxis
- 2:14 - Career Origins: Industrial Engineering, Supply Chain & Excel Macros
- 6:20 - Career Pivot: From Business Analyst to Data Engineering
- 7:48 - Analyst Skills as a Foundation for Data Engineering
- 8:06 - Docker & Terraform: Learning Curve for Data Practitioners
- 8:18 - Tools & Low-Code Beginnings: Excel, Alteryx, Tableau
- 11:13 - Retail & Warehousing Experience: Forecasting, Preload Optimization
- 21:57 - Digital Data Warehousing: Data as Inventory and Pipelines
- 22:36 - Modern Data Stack: ELT, dbt, BigQuery and Orchestration
- 24:34 - Operational Differences: Change Velocity, Monitoring, and Tests
- 27:50 - Metric Trees & Data Specs: Translating Business Requirements for FinOps
- 29:56 - Building a Digital Warehouse: Stack Choices and Open-Source Tools
- 31:40 - FinOps Overview: Cloud Cost Optimization for SaaS Platforms
- 34:15 - Vendor Negotiations & Reservation Instances for Cost Savings
- 36:11 - Cloud Cost Modeling: VM Sizing, Storage Tiers and Multi-Cloud Comparison
- 39:03 - Demand Forecasting Analogy: Inventory Planning Applied to Cloud Capacity
- 40:18 - FinOps Foundation, Cost Tagging & Accountability Best Practices
- 44:41 - OUCS & Standardizing Cloud Cost Reporting Across AWS/GCP/Azure
- 46:17 - FinOps Processes: Parallels with DevOps, DataOps and CI/CD
- 48:01 - Staff Data Engineer Responsibilities: Technical & Strategic FinOps Work
- 50:25 - Continuous Learning: Georgia Tech Master’s, dbt, Python and Applied Analytics
- 56:05 - Career Advice: Certifications, Mentorship, Community and Time Management
- 59:32 - Closing Remarks & Key Takeaways