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evan-gloria/README.md

☁️ Evan G. | Principal Data Professional & AI Solutions Architect

Building secure, enterprise-scale data platforms and FinOps-optimized AI architectures.

Hi, my name is Evan. 👋

With 11+ years of experience across Senior and Principal level roles in both Data Engineering and Data Analytics, I specialize in modernizing legacy ecosystems (Teradata, Oracle, Hadoop) into scalable, cloud-native platforms on AWS, Azure, and GCP.

Currently, I am architecting Serverless Data Pipelines and Applied Generative AI systems—turning massive enterprise datasets into actionable, grounded intelligence using open table formats (Apache Iceberg) and production-grade LLMs (Claude 3, Titan). My core focus remains bridging the gap between complex architectural design and tangible business value.

🏗️ Featured Project

🧠 Customermind AI - AI Microservices Marketing Hub (GCP)

An event-driven, LLM-powered microservices architecture for deterministic marketing orchestration and predictive customer intelligence on Google Cloud.

  • Stack: FastAPI, Vertex AI (Gemini Flash), BigQuery ML (K-Means), Streamlit, Cloud Run.
  • Impact: Decouples AI reasoning from data extraction using an Orchestrator pattern to eliminate LLM hallucinations, enabling zero-trust campaign generation and real-time audience viability forecasting.

📈 Real-Time Crypto Market Data Streaming (AWS)

A serverless data engineering pipeline for streaming high-velocity cryptocurrency market data into a modern transactional data lakehouse.

  • Stack: Amazon Kinesis Data Firehose, Apache Iceberg, AWS Glue, Amazon S3, Amazon Athena.
  • Impact: Implements a scalable, low-latency streaming architecture capable of handling high-throughput financial data with zero idle compute costs and ACID transaction compliance.

⛏️ WAMEX Serverless RAG Assistant (AWS)

An event-driven, serverless RAG pipeline deployed via AWS SAM, utilizing Amazon Bedrock, AWS Lambda, and a stateless S3 FAISS index to extract insights from unstructured geological reports.

  • Stack: Amazon SQS, AWS Lambda, Amazon Bedrock (Claude 3 Haiku & Titan), FAISS, Streamlit, Amazon S3, AWS SAM.
  • Impact: Delivers grounded information extraction with a scale-to-zero architecture, eliminating idle compute costs by utilizing S3 as a stateless vector store.

🚄 Real-Time Sydney Transit Analytics (GCP)

An event-driven, serverless Medallion architecture on Google Cloud.

  • Stack: Cloud Run, BigQuery, GCS, PySpark, Apache Iceberg, Looker Studio.
  • Impact: Processes real-time GTFS telemetry from Transport for NSW into a modern lakehouse format with zero idle compute costs.

  • 🧠 Certifications:

    • 🏆 AWS Certified Solutions Architect – Associate (SAA-C03)
    • 🏆 Microsoft Certified: Azure AI Engineer Associate (AI-102)
    • 🏆 AWS Certified AI Practitioner (AIF-C01)
    • 🏆 Google Cloud Certified: Generative AI Leader

  • 🛠️ Building: Serverless Medallion architectures and scalable RAG pipelines on GCP and AWS

  • 🔭 Focus: Customer Engineering, Enterprise GenAI, Apache Iceberg, and Cloud FinOps

  • 🚀 Future plans: Scaling real-time analytics with BigQuery BigLake and exploring multi-modal Vertex AI agents

🛠️ Technologies & Tools

Cloud & Data Warehousing GCP BigQuery AWS Azure

Engineering & Orchestration AWS Lambda Amazon API Gateway AWS SAM Amazon SQS Python Apache Spark Docker Terraform Apache Airflow

Analytics & AI Amazon Bedrock Anthropic LangChain Streamlit SQL Looker

📫 Let’s connect:
Feel free to reach out for collaboration, multi-cloud architecture discussions, or a good AI/ML chat!

Pinned Loading

  1. customermind-ai-microservices customermind-ai-microservices Public

    A distributed, LLM-powered microservices architecture for deterministic marketing orchestration on Google Cloud.

    Python 1

  2. wamex-rag-assistant wamex-rag-assistant Public

    Serverless RAG architecture for WAMEX geological reports using FAISS, S3, and Bedrock. Cost: Zero idle compute.

    Python

  3. nsw-transit-gcp-serverless nsw-transit-gcp-serverless Public

    A serverless, event-driven data engineering pipeline on Google Cloud (Medallion Architecture) for real-time Transport for NSW transit analytics.

    Python 1

  4. nsw-transport-lakehouse nsw-transport-lakehouse Public

    A scalable Data Lakehouse architecture for NSW Transport analytics. Implements ACID transactions, Time-Travel, and Schema Evolution using Apache Iceberg and PySpark on AWS S3.

    Python

  5. crypto-market-data-pipeline crypto-market-data-pipeline Public

    A real-time streaming data pipeline POC ingesting high-velocity WebSocket tick data via Kafka, micro-batching to an S3 Data Lake, and cataloged by AWS Glue for serverless Athena queries.

    Python

  6. titanic-survival-prediction titanic-survival-prediction Public

    Kaggle Competition for Titanic ML Survival Prediction: https://www.kaggle.com/competitions/titanic/overview

    Jupyter Notebook