Senior Python Engineer (Technical Lead)

Otto Tamas Pet Care Services Marketplace

• The client, a leading online marketplace for pet care services, was facing challenges in managing increased traffic and transaction volumes, particularly during peak times and promotional events on critical parts of their system.
• Lowered customer support storage costs by 30% by cleaning up waste tickets and implementing automations to prevent storage build-up in the future.
• Achieved legal compliance by automating the reruns of background checks required due to legislative changes, protecting the company from significant legal risks.
• Increased team productivity and work quality by 30% by enhancing retrospectives to be more visual and interactive, promoting a growth mindset, coaching agile best practices, and establishing team agreements.
• Skills: Python, Django, Celery, RabbitMQ, MemCached, MySQL, React, React Native, Docker, Kubernetes, AWS

Cloud Provisioning Platform

• The client, a major automobile company, was struggling to transition its manual operations teams to an automated solution for provisioning tailored cloud infrastructure across its IT departments to reduce delivery times and costs.
• Reduced the go-to-market time from 2 years to 1 year by refining the client’s architectural roadmap and development plan, improving the company’s ability to quickly adapt to market demands.
• Improved development time and code quality by 30% through creating a tailored development framework and coaching all 6 product teams on architecture, development, and a test-first approach.
• Increased deployment frequency by 50% and reduced production incidents by 40% by implementing a feature flagging system, enabling continuous delivery and safe, efficient release of new features.
• Skills: Python, FastAPI, Flask, SQLAlchemy, PostgreSQL, Azure, Pulumi, Celery, Redis, RabbitMQ, Kafka, MkDocs, Ruff, Docker, Kubernetes, SAFe

Simcenter 3D Pre- and Post-processing

• The client, a leading engineering software company, faced challenges with inefficient and lacking pre- and post-processing capabilities in Simcenter 3D, which impacted its ability to meet client needs.
• Achieved a 20% performance improvement in post-processing capabilities by optimizing memory usage and implementing more efficient data handling algorithms.
• Increased customer satisfaction by 30% by opening up post-processing capabilities for customer extensions using their preferred programming languages.
• Filled the gap for 80% of pre-processing customers by providing an automation tool for applying the results of a simulation as loads for the next simulation.
• Skills: Python, C++14/17, STL, OpenGL