Python Engineer | AI Agents, ETL Pipelines, Web Scraping & Data Automation | Founder of OhmFrame AI | Building Scalable Systems That Run in Production, Not Just Demos

I am a Data Engineer and Python Automation Specialist with 7+ years of experience building production-grade systems that solve real business problems. My background combines deep technical expertise in data engineering, AI agent development, and computer vision with a Principal Mechanical Engineer foundation that gives me a unique systems-thinking approach to complex technical challenges. My core expertise spans four areas: data engineering (ETL/ELT pipelines with Airflow, dbt, Snowflake, BigQuery, PostgreSQL, and MongoDB), Python automation (web scraping with Selenium and Playwright, workflow orchestration, API integrations, and scheduled reporting systems), AI and LLM integration (autonomous agents, RAG systems, prompt engineering, and multi-agent workflows using OpenAI and Anthropic APIs), and computer vision (real-time object detection with YOLOv8, OpenCV, and TensorRT optimized for edge deployment on NVIDIA Jetson and Raspberry Pi). I am the founder of OhmFrame AI, a live SaaS platform delivering autonomous engineering AI agents. This is not a side project or proof of concept. It is a production system serving real users, which reflects my commitment to building solutions that work reliably at scale. My GitHub profile (dawarazhar11) showcases 95+ repositories and 364 stars, demonstrating consistent, active contribution to the developer community. What sets me apart is the combination of hardware and software engineering experience. At DG Matrix, I spent 7+ years as Principal Mechanical Engineer working on power electronics systems and contributing to $20M in Series A funding. This cross-domain background means I understand system-level constraints, performance optimization, and production reliability in ways that pure software developers often overlook. I have applied this mindset to achieve 10-15 FPS real-time processing on resource-constrained edge devices and to build data pipelines that handle messy, real-world data without breaking. I work across AWS, GCP, and Azure, implement CI/CD pipelines, version control, automated testing, and monitoring as standard practice on every project. Whether you need a greenfield data warehouse, an AI-powered automation system, a web scraping pipeline, or a computer vision solution for edge deployment, I deliver clean, documented, production-ready systems. I value clear communication, realistic timelines, and delivering exactly what I commit to. Every project includes proper documentation, knowledge transfer, and ongoing support to ensure you are never left with a black box you cannot maintain.

Work Terms

Availability and Communication: I am available for both hourly and fixed-price engagements. My standard working hours are Monday through Friday, 9 AM to 6 PM PKT (UTC+5), with flexibility for urgent requests and overlap with US, UK, and European time zones. I respond to all messages within 4 hours during business days and provide regular progress updates through your preferred communication channel, whether that is Slack, Zoom, or Guru messaging. Project Workflow: Every engagement begins with a clear scope discussion where I outline deliverables, timeline, and milestones before any work begins. For hourly projects, I provide detailed time logs and weekly progress summaries. For fixed-price projects, I break work into milestones with defined deliverables so you have visibility at every stage. I use Git version control on all projects, and you receive the complete codebase. Rates and Payment: My hourly rates range from $45 to $60 depending on project complexity and domain. Data engineering and automation projects start at $45/hr, while AI agent development and specialized computer vision work is $55-60/hr. Minimum project budget is $300. For long-term or recurring engagements, I offer discounted retainer arrangements. I work exclusively through Guru SafePay for mutual protection. Deliverables and Quality: All code I deliver is clean, documented, and production-ready with proper error handling, logging, and testing. Final deliverables include source code, setup instructions, architecture documentation, and a handoff session if needed. I offer 14 days of post-delivery bug fixes at no additional charge to ensure everything runs smoothly after deployment. Confidentiality: I am happy to sign NDAs before project discussions. All client data and intellectual property remain strictly confidential, and I never reuse proprietary code or share project details without explicit permission.