Joel Macaroncio Jr.
Data Engineer, AI Developer & Tech Strategist
Empowering businesses with strategic planning, scalable data pipelines, and intelligent AI solutions. I turn complex data into actionable insights and build robust web applications.
Bridging Data, AI, and Business Strategy
Hello, I'm Joel Macaroncio Jr.
With a strong background in data engineering and intelligent systems, my primary goal is assisting business owners with strategic planning using my core skills. Let's transform your raw data into automated, AI-driven solutions that scale.
Whether it's building performant, multi-tenant dashboards, implementing automated workflows, or advising on technical roadmaps, I combine structural rigor with modern web aesthetics.
What I Can Do For You
I help businesses develop data-driven ideas into production-ready Web and Mobile applications in the fastest and most efficient way possible.
Tools & Technologies
The specialized tools I utilize to orchestrate data pipelines, construct robust applications, and manage agile enterprise workflows.
Data & Backend
Frontend & Mobile
AI & Automation
Project Management & Comm
Core Skills
My technical toolkit is focused on data engineering, automation, AI integration, and full-stack web development.
Professional Experience
Data Engineering Lead / Analyst
Accenture
Leading data engineering projects using Google BigQuery. Architecting robust data pipelines, enabling automation via Power Automate, and delivering actionable analytics that drive business strategy.
Digital Marketing & Analytics
Digital Marketing Agency
Architected tracking solutions, managed marketing automation, and generated actionable business intelligence reporting to optimize campaign performance and ROI.
Operations & Management
Resorts World Manila
Built a strong foundation in operations management, structured corporate processes, and oversaw early technical integrations for improved efficiency.
Featured Projects
A selection of my recent developments combining scalable data architecture with modern web design.
Enterprise Data Warehouse Architecture & Optimization
The Challenge
An organization faced challenges with disorganized datasets spread across multiple platforms, leading to fragmented data sources. This resulted in inefficient query performance, high latency, and significantly rising Google Cloud Platform (GCP) costs.
Technical Stack
The Solution: Scalable BigQuery Modeling
I architected a centralized data warehouse using a multi-tiered approach to ensure data quality and performance, moving from disorganized raw data to highly optimized reporting structures.
Tiered Architecture
Implemented a Bronze-Silver-Gold (Landing-Staging-Production) flow to maintain clean lineage and robust data transformations.
Schema & Modeling
Designed a robust Star Schema. Utilized nested and repeated fields (STRUCT/ARRAY) for denormalization to minimize heavy JOIN operations.
Cost Control & Performance
Applied strict table partitioning by Date and clustering by key dimensions, drastically optimizing data scanning and reducing overhead.
Automated Pipeline
Integrated automated logic for daily ETL refreshes, ensuring the reporting layers are continually updated with zero manual intervention.
The Impact
- Efficiency & Cost: Achieved a 30% reduction in query costs and a significant decrease in processed data volume.
- Speed: Reduced report loading times from minutes to sub-second latency for executive-level dashboards.
- Scale: Built a robust framework capable of handling millions of rows daily without any performance degradation.


