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Previous work has involved data analytics, SQL reporting, high-volume data pipelines, API development, data visualization, and ETL/ELT. My solutions emphasize reliability, efficiency, and simplicity. The databases and programming languages that I use most often are PostgreSQL, MongoDB, Redshift, Snowflake, BigQuery, MySQL, Python, and Node.js, but I have experience with others. For data visualization, I use Tableau and develop custom solutions.

I help companies move, process, and use their data on AWS — from event-driven ETL pipelines to RAG-powered AI applications. For the past 4+ years I've built exactly that at the U.S. Securities and Exchange Commission, handling high-volume financial data. THREE THINGS I DO 1. DATA ENGINEERING — Design and build ETL/ELT pipelines with Apache Airflow, PySpark, AWS Glue, and Redshift/Iceberg. Batch or event-driven, greenfield builds or rescuing pipelines that keep breaking. 2. CLOUD ARCHITECTURE (AWS) — Architect serverless and containerized systems with Lambda, ECS, S3, and DataSync, all as infrastructure-as-code (AWS CDK, CloudFormation). Migrate legacy on-prem workloads to AWS with CI/CD from day one. 3. AI & LLM APPLICATIONS — Build RAG systems with vector search (Qdrant), LLM-powered document analysis, and AI features shipped inside real products (Python, Next.js, OpenAI API). RESULTS I'VE DELIVERED • Cut data availability from ~1 hour to minutes with event-driven AWS pipelines (SEC) • Reduced deployment cycles from 9 weeks to 4 by automating CI/CD for AWS Glue ETL jobs (SEC) • Built a private RAG document-Q&A system over internal docs — semantic search with no data leaving the org • Saved 75 analyst-hours per week by automating manual data workflows (Comcast) TECH STACK • Languages: Python, SQL, TypeScript/JavaScript, R, Golang • Data Engineering: Apache Airflow, PySpark, AWS Glue, Pandas, NumPy, Alteryx • AWS Cloud: S3, Lambda, ECS, EC2, Athena, Redshift, Iceberg, DataSync, RDS/Aurora, DynamoDB, SNS, CDK, CloudFormation, SAM, LocalStack, CloudWatch • AI / LLM: LLM API(Anthropic, Gemini, OpenAI), Vector DB, RAG pipelines, AI-assisted development with Claude Code & Cursor • Databases: PostgreSQL, MySQL, Redshift, MongoDB, Neo4j, DynamoDB, Supabase • Web & APIs: React, Next.js, Node.js, FastAPI, Flask, Prisma • DevOps: Docker, GitHub Actions, Bamboo, Splunk, Jupyter CERTIFICATIONS • AWS Certified Solutions Architect • AWS Certified Data Engineer HOW I WORK Clear communication, tested code, and documentation your team can actually maintain. Everything I build is infrastructure-as-code — reproducible in your environment, no black boxes, no key-person risk. Tell me about your data stack, your cloud setup, or the AI feature you want to ship — I'll reply with a concrete plan for how I'd build it.

I am a Los Angeles-based Professional with 17+ years of work experience where I took roles of Full Stack Developer, Project Manager, Solutions Architect, Team Lead, DevOps Engineer, Project Consultant, Cloud Consultant, Cloud Architect, etc. I have a rich portfolio of Web and Mobile Apps(both iOS and Android). ***************** I have led Projects for well-known companies like Sony Pictures, Paramount Pictures, 20th Century Fox, Prince Cruise Line(PCL), Masimo, and Creative Artist Agency. ***************** As a Full Stack Developer/Team Lead/Project Manager/Solutions Architect I have extensive experience with a Web application, Mobile Applications, Desktop Application Development, UI/UX Design, Tech Support, Cloud Architect, and Consulting Projects involving technologies like Wordpress, PHP, Java, Python, C#, Javascript, React, Angular, Node.js, Express.js, Shopify, Swift, Objective-C, React Native, AWS, GCP, Microsoft Azure, etc. - Build and develop the project team to ensure maximum performance, providing purpose, direction, and motivation. - Lead projects from requirements definition through deployment, identifying schedules, scopes, budget estimations, and project implementation plans, including risk mitigation. - To coordinate internal and external resources, ensuring projects remain within scope, schedule, and defined budgets, in collaboration with project staff from various functional departments. - Analyze project progress and, when necessary, adapt scope, timelines, and costs to ensure that the project team adheres to project requirements. - Establish and maintain relationships with appropriate client stakeholders, providing day-to-day contact on project status and changes As DevOps/Cloud Engineer I have extensive experience in designing, implementing, and maintaining complex Cloud-based infrastructure with a focus on security, scalability, and high availability. AWS Services: Deployment Automation: Proficient in automating deployment processes using AWS CloudFormation, Terraform, and Ansible to reduce errors and improve speed. Continuous Integration and Delivery: Skilled in setting up CI/CD pipelines using AWS CodePipeline, AWS CodeBuild, and Jenkins for automated build, test, and deployment processes. Monitoring and Alerting: Capable of setting up monitoring systems using AWS CloudWatch, Prometheus, and Grafana to identify performance issues proactively. Security and Compliance: Knowledgeable in implementing security best practices and automated compliance checks using AWS Config and AWS Security Hub. Cost Optimization: Experienced in optimizing AWS spending using tools like AWS Cost Explorer, AWS Budgets, reserved instances, spot instances, and auto-scaling. Microsoft Azure Services: DevOps Strategies: Proficient in designing and implementing effective DevOps strategies using Microsoft Azure for continuous integration, delivery, and deployment. Infrastructure Provisioning and Configuration: Experienced in provisioning and configuring Azure infrastructure using tools like Azure Resource Manager (ARM) templates and Terraform. Continuous Integration and Continuous Deployment (CI/CD): Skilled in establishing CI/CD pipelines using Azure DevOps for automated build, test, and deployment processes. Automation and Orchestration: Capable of automating tasks and processes using PowerShell, Azure CLI, Azure Automation, and Azure Logic Apps to streamline operations. GCP Services: Deployment Automation: Proficient in automating deployment processes using tools like Google Cloud Deployment Manager and Terraform to ensure consistency and reliability. Continuous Integration and Delivery: Skilled in setting up CI/CD pipelines using Cloud Build and Jenkins on GCP for automated testing, building, and deployment of applications. Monitoring and Alerting: Capable of implementing monitoring and alerting systems using Stackdriver Monitoring and Stackdriver Logging to identify and resolve issues promptly. Security and Compliance: Knowledgeable in implementing security controls and compliance standards using GCP Identity and Access Management (IAM) and Security Command Center. Cost Optimization: Experienced in optimizing costs on GCP using tools like Cost Explorer and Budgets, as well as utilizing features like sustained use discounts and preemptible VMs to minimize expenses. *****************

🏆 Top Rated Full Stack Developer with 23 years of experience🏆 With 100% success rate 💯 In the top 3% of performers on Upwork. A Full Stack Developer who has worked with organizations like Sysco, Yale University, and Williams Energy with 3000+ hours of experience just on Upwork. As a Full Stack Developer, I pride myself on my ability to work hard to solve challenging and complex problems/issues that my clients face and deliver my projects on schedule. I am confident that my skills and abilities as a Top Rated Full Stack Developer will be a great asset to your project. Here are some of the services that I offer as a full stack developer, for your reference: - Full life cycle of the software design process including requirements definition, prototyping, proof of concept, design, interface implementation, testing, and maintenance. - Administering SQL Server databases which includes scheduling backups and performance tuning. - Developing Windows, Web, and Window Services applications. - Delivering business solutions and improving business processes. - Extensive knowledge in enterprise system installation, configuration, administration, and integration. - Extracting data from proprietary databases, transforming the data, and loading it into a centralized data warehouse for reporting. It is my ability, skills, and passion for what I do that have helped me build long-lasting working relationships with my clients and I hope that I can build such a relationship with you as well. I look forward to finding a great solution for you!

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.

Hi, I'm Owais. I've spent 7+ years building data systems across enterprise and startup environments. I've set up entire data platforms from end-to-end on AWS, Azure, and GCP, including in SOC 2 and HIPAA environments. I've built ETL pipelines that don't break at 3 AM, modeled warehouses that survive contact with real business logic, and shipped dashboards people actually open. These days I help growth-stage startups build analytics platforms around AI without bleeding money on it. Natural language to SQL, agents that surface insights instead of waiting to be asked, automated anomaly detection, the kind of features your customers are starting to expect. Most AI-in-analytics projects don't fail because the model isn't good enough. They fail because the foundation underneath it is a mess. A well-documented dbt project does more for AI accuracy than a bigger LLM, and if your dashboards aren't getting opened, adding AI on top doesn't change anything. If you're trying to build AI-powered analytics and want someone who's done the unglamorous work that makes it actually useful, let's talk.