Pavel Grishin
Moscow, Russia
Pavel Grishin
Python web developer
Category : Web development
Backend Python developer with experience building high-load internal systems and automation tools. I design and develop reliable APIs, microservices, and database-driven applications using FastAPI and PostgreSQL. Experienced with event-driven architectures, asynchronous processing, and service-to-service communication. I focus on performance, data consistency, and predictable system behavior, always aligning technical solutions with business requirements.
Working hours
- Monday:08h00 To 18h00
- Tuesday:08h00 To 18h00
- Wednesday:08h00 To 18h00
- Thursday:08h00 To 18h00
- Friday:08h00 To 18h00
- Saturday:Not available
- Sunday:Not available
Worked on the development and maintenance of a Warehouse Management System (WMS) to automate warehouse operations for one of the largest e-commerce platforms. Involved in building high-load backend services with a focus on reliability, scalability, and data consistency.
Responsibilities & Achievements.
Designed and developed a microservice architecture using Python (FastAPI). Built and optimized PostgreSQL databases for new business requirements:
- Followed ACID principles
- Performed query optimization using EXPLAIN ANALYZE
- Implemented indexing strategies
- Worked with the database via SQLAlchemy
- Implemented event-driven architecture (EDA) using Apache Kafka for reliable inter-service communication without data loss
- Wrote and maintained Dockerfiles
- Non-root container execution
- Health checks for Kubernetes integration
- Proper .gitignore configuration
- Used Git for version control and team collaboration
Worked in an Agile / Scrum environment.
Team size: 7 developers.
Technology Stack: Python 3.11, FastAPI, SQLAlchemy, PostgreSQL, Apache Kafka, Redis, Docker, PyTest.
Responsibilities & Achievements.
Designed and developed a microservice architecture using Python (FastAPI). Built and optimized PostgreSQL databases for new business requirements:
- Followed ACID principles
- Performed query optimization using EXPLAIN ANALYZE
- Implemented indexing strategies
- Worked with the database via SQLAlchemy
- Implemented event-driven architecture (EDA) using Apache Kafka for reliable inter-service communication without data loss
- Wrote and maintained Dockerfiles
- Non-root container execution
- Health checks for Kubernetes integration
- Proper .gitignore configuration
- Used Git for version control and team collaboration
Worked in an Agile / Scrum environment.
Team size: 7 developers.
Technology Stack: Python 3.11, FastAPI, SQLAlchemy, PostgreSQL, Apache Kafka, Redis, Docker, PyTest.
- 🇬🇧 English
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