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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.

Updated on 3rd june 2026 I build AI systems that act as a "force multiplier" for executives and their teams. Case Study: Built an enterprise AI analytics and reporting platform for a multi-company organization with 1,000+ users, integrating Salesforce, Slack, Asana, Google Drive, and Google Sheets into a unified AI ecosystem. Leveraged MCP, RAG, Qwen, LangChain, Pinecone, and Python-based knowledge ingestion pipelines to enable enterprise search, automated reporting, cross-platform data retrieval, and AI-driven decision support, significantly improving operational efficiency and reducing manual workflows. Most AI implementations fail because they are disconnected from the actual data employees use every day. I specialize in building Agentic Workflows on Azure that bridge the gap between your raw data (Slack, Email, Meetings) and actionable business intelligence. My Signature Achievement: 1. The Virtual COO (Executive Intelligence): Developed an AI "Chief of Staff" that consolidates Slack, Gmail, and meeting transcripts into a single decision-engine. Built with Azure OpenAI and n8n, it identifies bottlenecks and prioritizes tasks so nothing drops through the cracks. 2. AI Clinical Assistant (Scaled Healthcare): Built a RAG-based diagnostic support tool currently used by 300,000+ practitioners in Europe. It leverages LangChain and Pinecone to analyze patient patterns in real-time, surfacing evidence-based treatment suggestions in Portuguese while staying strictly compliant with local privacy laws. 3. Private Vision Pipeline (Secure Taxation): A client needed to extract data from handwritten tax documents but couldn't use OpenAI/Claude due to privacy. I deployed a 2B parameter Vision Language Model on private servers. The Result: 98% accuracy on handwritten text and a 14,000% increase in processing speed (from 480 docs/day manually to processing a doc every 5 seconds). What I can do for you: Azure & Private AI: Whether you need Azure AI Foundry or a fully private, locally-hosted LLM to keep your data secure, I’ve built both. Agentic Automation: I don't just "connect APIs." I build agents that think, categorize, and act—using n8n, Python, and custom hooks. Production-First Data: As a Microsoft Certified Data Engineer, I ensure your data is clean before the AI touches it. No "garbage in, garbage out." The Tech Stack: Azure (OpenAI/Fabric) • LangChain • n8n • Python • Pinecone • SQL • dbt • Vision-Language Models (VLM) Why $30/hr? I am a veteran engineer, but I am new to the Upwork ecosystem. My current rate reflects my goal to build a 5-star reputation on this platform quickly. You are getting enterprise-grade architecture at a "reputation-building" price. Let’s hop on a call to talk about your workflow. I’ll tell you exactly what’s possible, and more importantly, what’s a waste of your money. Uwais

Cloud Solution Architect with engineering experience in Cloud SQL Big Data technologies including Data Architecture to support various Business Intelligence needs. Solution Architect in Technical Teams on Cloud Data Solutions into various Cubes, Data Marts, and ERP Systems. Developed data structures for business using various Analysis Services Cubes, BI Dashboard, and Scorecards. Recent experiences include developing multiplayer AI Platform with Generative AI using AWS Bedrock for back-office CareManagement application including HealthCare. Implementations included Anthropic Claude model & Twilio Integration for Client Onboarding, Authentication, and Call Flow Management. Cloud Services Database include Snowflake Data Cloud, Azure Cloud, Go/Language (JSON and yaml) with Anaconda python programming. Migrated Data Lakes from on-prem up to SnowFlake using SnowPipe and SnowSQL using command line scripts using AI methods. Implemented standards and data designs for HIPAA, SOX, regulatory, compliance, financial, reporting, and auditing. Next generation AI development with Anthropic Claude Code, ChatGPT, Gemini, etc.

𝐈 𝐛𝐮𝐢𝐥𝐝 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧-𝐠𝐫𝐚𝐝𝐞 𝐝𝐚𝐭𝐚 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦𝐬 𝐟𝐨𝐫 𝐜𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐝𝐞𝐚𝐥𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 𝐛𝐫𝐨𝐤𝐞𝐧 𝐩𝐢𝐩𝐞𝐥𝐢𝐧𝐞𝐬, 𝐬𝐜𝐚𝐭𝐭𝐞𝐫𝐞𝐝 𝐬𝐲𝐬𝐭𝐞𝐦𝐬, 𝐬𝐥𝐨𝐰 𝐫𝐞𝐩𝐨𝐫𝐭𝐢𝐧𝐠, 𝐚𝐧𝐝 𝐮𝐧𝐫𝐞𝐥𝐢𝐚𝐛𝐥𝐞 𝐦𝐞𝐭𝐫𝐢𝐜𝐬. I’m a Senior Data Engineer with 10+ years of experience building cloud data platforms, ETL/ELT pipelines, lakehouses, warehouses, and analytics-ready data layers using Microsoft Fabric, Snowflake, AWS, BigQuery, dbt, Python, SQL, Airflow, Fivetran, Airbyte, and Databricks. My focus is not just moving data from point A to point B. I design reliable data systems that are automated, scalable, well-modeled, and trusted by business teams. 𝐖𝐡𝐚𝐭 𝐈 𝐡𝐞𝐥𝐩 𝐰𝐢𝐭𝐡 ✅ 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐅𝐚𝐛𝐫𝐢𝐜 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 Lakehouse, Warehouse, Dataflows Gen2, pipelines, notebooks, semantic models, Medallion architecture, and Power BI-ready data layers. ✅ 𝐂𝐥𝐨𝐮𝐝 𝐃𝐚𝐭𝐚 𝐖𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 Snowflake, BigQuery, Redshift, Databricks, PostgreSQL, SQL Server, and Azure Synapse architecture. ✅ 𝐄𝐓𝐋/𝐄𝐋𝐓 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 API ingestion, database replication, SaaS integrations, file ingestion, batch jobs, incremental loads, and scheduled workflows. ✅ 𝐝𝐛𝐭 & 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠 Staging, intermediate, marts, incremental models, tests, documentation, metric definitions, and business logic standardization. ✅ 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 & 𝐎𝐫𝐜𝐡𝐞𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 Airflow, Dagster, AWS Lambda, Glue, Step Functions, ADF, CI/CD, monitoring, retries, alerts, and production workflow automation. ✅ 𝐃𝐚𝐭𝐚 𝐐𝐮𝐚𝐥𝐢𝐭𝐲 & 𝐆𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 Deduplication, reconciliation, schema drift handling, validation rules, MDM, Golden Record logic, RBAC, access control, and audit-ready reporting layers. 𝐑𝐞𝐜𝐞𝐧𝐭 𝐩𝐫𝐨𝐣𝐞𝐜𝐭 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞: 𝐌𝐢𝐜𝐫𝐨𝐬𝐨𝐟𝐭 𝐅𝐚𝐛𝐫𝐢𝐜 𝐞𝐧𝐭𝐞𝐫𝐩𝐫𝐢𝐬𝐞 𝐚𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦 Built a centralized Fabric platform with Lakehouse, Warehouse, Dataflows, pipelines, semantic models, and Power BI reporting layers for a global organization with fragmented reporting sources. 𝐍𝐞𝐚𝐫 𝐫𝐞𝐚𝐥-𝐭𝐢𝐦𝐞 𝐒𝐧𝐨𝐰𝐟𝐥𝐚𝐤𝐞 𝐝𝐚𝐭𝐚 𝐩𝐥𝐚𝐭𝐟𝐨𝐫𝐦 Designed operational pipelines into Snowflake with incremental ingestion, schema change handling, deduplication, retries, and reliable dbt-based reporting models. 𝐌𝐨𝐝𝐞𝐫𝐧 𝐒𝐚𝐚𝐒 𝐝𝐚𝐭𝐚 𝐬𝐭𝐚𝐜𝐤 Centralized HubSpot, Stripe, GA4, Google Ads, Salesforce, MongoDB, and product data into BigQuery/Snowflake using Fivetran, Airbyte, dbt, Dagster, and Metabase. 𝐋𝐞𝐠𝐚𝐜𝐲 𝐦𝐢𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐭𝐨 𝐜𝐥𝐨𝐮𝐝 𝐰𝐚𝐫𝐞𝐡𝐨𝐮𝐬𝐞 Led migrations from SQL Server, SAP BW, Oracle, Hadoop, and on-prem systems into modern cloud warehouses with optimized performance and automated workflows. 𝐀𝐖𝐒 𝐝𝐚𝐭𝐚 𝐚𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 Built automated workflows using S3, Lambda, Glue, Step Functions, IAM, SNS, CloudWatch, and Python to reduce manual reporting and improve pipeline reliability. 𝐓𝐨𝐨𝐥𝐬 𝐈 𝐰𝐨𝐫𝐤 𝐰𝐢𝐭𝐡 Microsoft Fabric, Snowflake, BigQuery, Redshift, Databricks, Azure Synapse, PostgreSQL, SQL Server, Oracle, SAP BW, Hadoop, dbt, Python, SQL, Airflow, Dagster, Fivetran, Airbyte, ADF, SSIS, Talend, AWS S3, Lambda, Glue, Step Functions, IAM, SNS, CloudWatch, Power BI, Tableau, Metabase, and Looker. You should reach out if you need a senior data engineer to: ✅ Build a cloud data warehouse or lakehouse ✅ Migrate legacy systems to Snowflake, Fabric, BigQuery, or AWS ✅ Fix unreliable ETL/ELT pipelines ✅ Design dbt models and trusted reporting layers ✅ Automate manual reporting workflows ✅ Integrate APIs, CRMs, ERPs, databases, and SaaS platforms ✅ Build production-ready data infrastructure for analytics and BI If your data stack is messy, slow, or hard to trust, send me a message. I’ll help you map the cleanest path from scattered systems to a reliable data platform.

SUMMARY Software engineer specializing in distributed systems, event-driven architecture, and multi-agent AI systems. At Johns Hopkins University's Project MUSE, independently architected a distributed content-launch platform and built AI worker pipelines that processed 15 million images at scale. Former small-business owner who brings an entrepreneurial, ownership-driven approach to engineering: identifying high-impact problems, shipping end-to-end solutions, and modernizing legacy systems without disrupting production. TECHNICAL SKILLS Languages: Python, Perl, JavaScript, TypeScript, SQL Frameworks: FastAPI, Flask, Django & Django DRF (limited), Angular, Node.js Architecture: Microservices, event-driven pub/sub, REST API design, real-time systems (WebSockets, long-polling) Data & AI: Redis, PostgreSQL, MySQL, MongoDB, Cassandra (limited), Pandas, NumPy, Scikit-learn, Azure OpenAI DevOps: Docker, Docker Swarm, Kubernetes (limited), Jenkins, GitLab CI/CD, NGINX, FusionAuth, Linux PROFESSIONAL EXPERIENCE Programmer Analyst — Johns Hopkins University Press, Project MUSE Aug 2022 – Present • Architected and built an event-driven content-launch platform (Angular, FastAPI, Redis pub/sub, Docker) that orchestrates book and journal launches through distributed workers, replacing manual multi-step publishing workflows. • Built AI worker pipelines processing 15 million images in 6 months, generating alt text and accessibility metadata via Azure OpenAI, bringing a multi-decade content archive into WCAG compliance ahead of a mandated June 2026 deadline. • Designed a real-time teams/channels system where staff chat and subscribe to platform events (e.g., “book launched for publisher X”), delivering operational visibility across departments. • Automated publisher access transitions from gated to open access with a rules engine that lets non-technical staff define business logic via JSON configuration. • Shipped a DOI Reservation SPA in vanilla JavaScript backed by a custom Perl REST API, plus Jenkins CI/CD pipelines with dockerized build workers. • Owned 8+ production features across the legacy stack (Perl CGI, MySQL, jQuery), modernizing UIs with SPA patterns and long-polling optimizations while maintaining zero-downtime operations. • Engineered a Perl ORM library with caching, indexing, and binary search for optimized access across 1.2 million records, achieving sub-30-second aggregations in a single-threaded monolith. • Designed a web-based email templating tool integrating Excel parsing, database queries, and live HTML previews. Senior Architect (Contract) — Perfeqta Jan 2024 – Jan 2025 • Delivered a working FusionAuth prototype in 4 days for multi-tenant enterprise software, then implemented a custom authorization system integrating existing privilege hierarchies to enable SSO, LDAP, JWT, and MFA. • Built a secure email- and SMS-based two-factor authentication system and coordinated multi-service user enrollment flows across Angular, .NET, and Node.js backends with PostgreSQL and MongoDB stores. Contract Developer — Silobuster / OpenReferral Mar 2023 – Aug 2023 • Deduplicated ~16,000 records for Maryland 211 in 4 weeks using a Python standardization library with ML-based deduplication, preserving the organization's funding on a state contract. Published on PyPI. EDUCATION & CERTIFICATIONS Master of Science, Computer Science — Ball State University (expected Nov 2026) — GPA 4.0 Coursework: Advanced AI, Cybersecurity, Data Visualization, Discrete Structures, Full-Stack Web Development PCPP – Python Certified Professional in Programming

Hey, I'm Brian 👋 I’ve helped businesses generate over $500K in additional revenue by implementing AI voice agents that answer calls, capture leads, and book appointments automatically. For another client, I built an AI phone agent that now handles 115+ calls per day, saving roughly 16 employee hours per week. A lot of small businesses do not have a lead problem. They have a response-time problem. When calls go unanswered, leads do not get a fast response and revenue slips through the cracks. I build AI Voice Agents that: ✅ Answer inbound calls 24/7 for after hours and overflow ✅ Lead qualification and routing ✅ Book appointments and reschedule without staff involvement ✅ Follow up with new inquiries instantly ✅ Reduce front desk and admin workload ✅ Integrate with existing systems AI Voice Agents are especially helpful in phone-heavy industries, including: Home services — HVAC, plumbing, electrical, roofing, pest control, restoration, landscaping Healthcare — OB/GYN, dermatology, primary care, physical therapy, chiropractic, optometry, Dental — general dentistry, cosmetic dentistry, orthodontics, oral surgery, pediatric dentistry Legal — personal injury, family law, criminal defense, immigration, estate planning, bankruptcy Real estate — brokerages, mortgage brokers, property management, investors, leasing teams These systems can also automate a lot of the work that happens after the call, including: ✅ Call summaries and transcripts ✅ CRM updates and lead routing ✅ Follow-up texts and emails ✅ Appointment confirmations and reminders ✅ Internal notifications for staff ✅ Workflow automation across tools like Twilio, GoHighLevel, Make, and n8n Tools and platforms I work with include Retell AI, Vapi, Eleven Labs, Twilio, GoHighLevel, Hubspot, Make, n8n, webhooks, APIs, and CRM integrations. If you're looking for an AI voice agent that improves response times, captures more leads, and reduces manual workload, send me a message and let’s talk through your use case. I look forward to working with you