Position: Python Developer
Category: Python
English level: fluent
Years of experience: 2


Software Engineer
Tasks:
Implemented a production-ready back-end infrastructure that supports DEV and PROD environments using Python on the Django REST Framework
Integrated new API endpoints using Django REST Framework (DRF) for file uploading and downloading subsetted CSV files after receiving indexes from the front-end
Leveraged third-party API endpoints for OAuth2 and downloading datasets
Implemented JSON Web Token (JWT) with OAuth2
Utilized Python ORM libraries like Django ORM
Created models and loaded data into the PostgreSQL database and AWS S3 bucket using the boto3 library
Performed creating, reading, updating and deleting (CRUD) operations on AWS RDS for PostgreSQL using psycopg2
Created docker images based on python and conda base images and synced up back-end with front-end in docker container
Improved the size of the conda docker image from 2GB to 800 MB
Use Pandas and Numpy array to do statistical analysis on data provided in CSV format
Generate dynamic graphs using libraries like Faerun, tmap, Scipy, rdkit, Pickle
Managed code versioning using GitLab and deployment to development and production servers
Debugged and troubleshot the web application
Covered unittest using PyTest framework, used advanced packages like Mock, patch, and factory-boy to perform unit testing and checked test coverage with coverage library
Followed PEP8 using black, flake8 and isort libraries
Implemented a production-ready web application using the Dash framework
Implemented dynamic column selection and interactive data visualization using the Plotly library
Refactored codebase to parse XML documents
Refactored existing API endpoints for downloading data from third-party providers using the requests library
Introduced parallel programming using the library asyncio, decreased extensive data downloading from 6 minutes to 30 seconds
Experienced in Agile methodologies, Scrum stories and sprints
Technologies:
AWS Web Services (ECR, S3 Bucket, RDS for PostgreSQL), Atlassian Confluence and Jira, HTML5/CSS, Javascript, Git and GitHub, Django, Django REST framework, Docker, Gitlab, CI/CD, PyTest, Python libraries (NumPy, Pandas, Matplotlib, Scikit Learn), Authentication/Authorization protocols: JWT, OAuth2, React.js, Relational Databases: PostgreSQL, Non-relational Databases: MongoDB, Basic Apache Airflow, SOAP, XML, JSON, REST API