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🚀 Ex-Meta / Yahoo | AI Full-Stack Engineer | GenAI, LLM, SaaS, APIs I build end-to-end AI products — from LLM-powered features to scalable full-stack systems. With 10+ years at Meta, Yahoo, and startups, I’ve shipped production systems used by millions and designed platforms that scale reliably. I focus on delivering real, usable AI applications — not just demos. ✅ What I Can Help You Build: • GenAI Applications: GPT / Claude integrations, AI copilots, workflows, prompt engineering • RAG Systems: chat over documents, knowledge bases, retrieval pipelines • Full-Stack AI Apps: frontend + backend + APIs + AI integration • AI Agents: tool-using agents, automation workflows • Backend Systems: scalable APIs, microservices, cloud architecture • AI SaaS: MVP → production-ready systems 💼 Experience Highlights: • Meta — built large-scale production systems • Yahoo — personalization systems serving billions of requests/day • Indeed / Workday — scalable backend and cloud platforms • Tech Lead — owned architecture and built systems end-to-end • Real-time systems processing TBs/day (Kafka, distributed systems) 📊 What You Get: • End-to-end builder (AI + full-stack + product) • Production-ready systems, not fragile prototypes • Scalable architecture from day one • Fast execution and clear communication 🔧 Tech Stack: AI: GPT-4/5, Claude, RAG, AI agents, prompt engineering Frontend: React, Next.js, TypeScript Backend: Python (FastAPI, Flask), Node.js, Java, Scala, APIs, microservices Cloud: AWS (S3, Lambda), serverless architecture Infra: Docker, Kubernetes, CI/CD Data: Spark, Kafka Databases: PostgreSQL, MySQL, MongoDB, Redis 🎯 Typical Projects: • AI chatbot / copilot • RAG over internal/company data • AI SaaS MVP • Full-stack GenAI applications • Workflow automation with LLMs Keywords: Generative AI, GenAI, LLM, GPT-4, GPT-5, Claude, OpenAI API, Anthropic Claude, RAG, Retrieval Augmented Generation, AI Agents, Prompt Engineering, AI Automation, Chatbots, Copilots, Python, FastAPI, Flask, Full-Stack Development, Frontend Development, Backend Development, React, Next.js, TypeScript, Node.js, API Design, REST APIs, GraphQL, Microservices Architecture, SaaS Development, Multi-Tenant Systems, Authentication, OAuth, JWT, Cloud Architecture, AWS, Serverless, Docker, Kubernetes, CI/CD, Distributed Systems, System Design, PostgreSQL, MySQL, MongoDB, Redis, Machine Learning, MLOps, Data Engineering, Apache Spark, Kafka Industries: AI Platforms, SaaS, Enterprise Software, AdTech, MarTech, E-commerce, Marketplaces, FinTech, Payments, Healthcare, HealthTech, Developer Tools, Productivity Tools, Analytics Platforms, Data Platforms, Media, Social Platforms

Most data pipelines don’t fail because of code. They fail because they weren't built for scale. With 8+ years of experience engineering data systems at companies like Microsoft and Coreweave, I help businesses move away from "brittle prototypes" to production-grade, scalable infrastructure. I don’t just move data; I build the "Source of Truth" that leadership and AI systems actually trust. 💬What I Solve for You: Productionizing AI Pipelines: Hardening Python prototypes into scalable RAG and LLM infrastructures (AWS/Azure). ➔Infrastructure-as-Code: Building automated, modular ETL/ELT pipelines that don't require daily manual fixes. ➔The "One-Source" Dashboard: Integrating messy data from APIs, SaaS (Shopify, HubSpot), and DBs into clean Snowflake/BigQuery layers. ➔Performance Recovery: Optimizing slow SQL queries and high-cost cloud warehouses to save you thousands in monthly spend. 🛠 Tech Stack: Languages: Python (FastAPI, Pandas, PySpark), SQL Cloud & Warehousing: AWS (Glue, Lambda, S3), Snowflake, BigQuery, Azure Orchestration: Airflow, dbt, GitHub Actions Data Ops: API Integrations, Vector DBs, Data Validation ✅ Why Me? 8+ Years Experience: I’ve seen what breaks at the enterprise level and how to prevent it in your startup. Speed over Perfection: I focus on shipping high-impact systems that drive revenue, not just technical documentation. Transparent Communication: You get regular updates and a partner who challenges requirements to find better solutions. Ready to clean up your data debt? 📩 Message me for a FREE 15-minute technical consultation. Let’s discuss your architecture and see if I’m the right fit for your system.

I’m an AI Full-Stack Data Engineer specializing in designing, building, and deploying end-to-end data systems that power analytics, machine learning, and AI-driven applications. I help companies turn raw, messy data into scalable, production-ready pipelines and intelligent systems. My focus is on building reliable data infrastructure, integrating LLMs into real-world products, and enabling data-driven decision-making through clean architecture and automation. I work across the full stack of data engineering from ingestion and transformation to model deployment and API integration, ensuring performance, scalability, and maintainability at every layer. Core expertise includes: Building scalable ETL/ELT pipelines (batch & real-time) Designing data architectures (data lakes, warehouses, lakehouses) LLM integration (OpenAI, LangChain, RAG systems, vector databases) API development (FastAPI, Flask, Node.js) Cloud platforms (AWS, GCP, Azure) MLOps & deployment (Docker, Kubernetes, CI/CD) Data processing frameworks (Spark, Pandas, Airflow, dbt) Database systems (PostgreSQL, MySQL, MongoDB, Snowflake, BigQuery) I prioritize clean code, system reliability, and business impact. Whether it’s building a full data platform from scratch or optimizing existing pipelines, I deliver production-grade solutions that scale.

🚀 Turning Data into Business Gold Hi, I’m Nelson — a Senior Principal Engineer with 24+ years in IT, specializing in data engineering, cloud architecture, and machine learning. I hold a master’s degree in Computer Science and an MBA, enabling me to bridge deep technical solutions with real business impact. I’m a Google Cloud Certified Professional Data Engineer and AWS Certified Solutions Architect – Professional, with hands-on experience across AWS, GCP, and OpenStack. I’ve led data and ML projects that power critical business decisions. 🔧 What I Do Best 🟨 Data Engineering • Build scalable ETL pipelines using SQL, dbt, Airflow • Work with Redshift, BigQuery, Snowflake, Databricks • Python, Pandas, Spark, Hadoop 🟨 Machine Learning • NLP, Sentiment Analysis, Classification Models 🟨 Cloud Specialist • Infrastructure on AWS, GCP, OpenShift, Ceph • DevOps, CI/CD, Linux, distributed storage systems 🏅 Certifications ✅ Google Cloud Professional Data Engineer ✅ AWS Solutions Architect – Professional ✅ Cloudera Certified Administrator for Apache Hadoop (CCAH) ✅ Red Hat Certified: OpenShift & OpenStack ✅ EMC Information Storage & Management 🧠 Skills Snapshot • Web & social media data analytics • Data modeling, warehousing, and ETL design • Hadoop, Spark, Kafka • Workflow orchestration with Airflow • Cloud-native architecture (AWS, GCP, Azure) • Relational & NoSQL DBs • Secure and compliant data design 📌 Services I Offer • Data pipeline development • End-to-end data architecture design • Cloud-based data solutions • Data warehouse implementation • Big data analytics and batch processing • Data quality and governance strategy 🌟 Highlight: Award-Winning Project 🏆 Best Big Data Paper Award – for using open datasets to predict market trends, recognized at Dell Technologies World. 💬 What Others Say “Nelson is very approachable and always willing to help. Whether it’s software development, big data analytics in the cloud, or ML projects—he delivers with expertise and curiosity.” “He gets things done. Whether it’s open-source tools or custom code on AWS, Nelson solves problems creatively and efficiently.” “Exceptional AWS skills, and incredibly patient. A true professional.” ✅ Why Work With Me I bring a strategic mindset to every project. You won’t just get code — you’ll get solutions that align with your business goals. I’m curious, detail-oriented, problem solver and relentless about delivering results. Let’s collaborate to unlock the full value of your data.

Software Development Engineer Core Competencies: • RESTful API, Web Services, Microservices • Programming language (JavaScript, PHP, Perl, Ruby, Java, Python, Go, .NET) • Java frameworks (Spring, Spring Boot) • Messaging (Apache Kafka, AWS SQS) • Big Data (Apache Spark, Apache Airflow, Sqoop, Presto/Trino, Apache Flink, Elasticsearch) • DB (SQL, NoSQL (Redis, Casandra, DynamoDB, BigTable)) • CI/CD • Monitoring/Observability • Testing Strategy • AWS • Code Review • Interview

PROFESSIONAL SUMMARY Data Analysis Expertise: Over 20 years of dedicated experience in data analysis, emphasizing the enhancement of healthcare quality. Data Integration with SSIS: Created and maintained SSIS packages, centralizing data from 9 sources into a comprehensive data warehouse. Cloud Data Warehousing: Successfully established a data model in AWS Redshift, utilizing S3 bucket storage for efficient cloud-based data warehousing. Amazon Web Services (AWS): Proficiently utilized various AWS services, including VPC, EC2, Redshift, RDS (Postgres), IAM, and S3. ETL Data Pipelines with Python: Developed Python scripts for ETL data pipelines, exemplifying skills showcased in my GitHub repository. Reporting and Visualization Tools: Proficient in leveraging reporting and visualization tools such as Tableau, PowerBI, and Python for Data Science. Key Highlights: Databricks Proficiency: Demonstrated proficiency in Databricks, utilizing notebooks and pyspark for advanced data engineering tasks. AWS Data Engineering Skills: Applied strong AWS data engineering skills, including the development of ETL jobs, data warehousing, and cloud storage. Extensive SQL Experience: Extensive experience in writing complex SQL queries, ensuring efficient data retrieval and analysis.