Python Backend Developer with 3+ Years Experience

Aastha Patel

PYTHON DEVELOPER

NC, USA • +1-262-***-**** • **************@*****.*** • LinkedIn

Python Developer with 3+ years of experience in building scalable backend applications, automation workflows, and data-driven systems using Python. Strong expertise in REST API development, microservices architecture, and data processing with FastAPI, Flask, Pandas, and SQL. Experienced in designing, deploying, and maintaining production-ready services using Docker, CI/CD pipelines, and cloud platforms such as Azure and GCP. Hands-on exposure to applied AI and NLP techniques, leveraged selectively to enhance automation, reporting, and analytics, while maintaining a core focus on clean, efficient, and reliable Python engineering. SKILLS

● Core Skills: Python, FastAPI, Flask, REST APIs, SQL, Pandas, AsyncIO, Docker

● Languages: Python, SQL, Java, HTML

● Python & Backend: Python (OOP, decorators, generators, context managers), REST API development, FastAPI, Flask, Asynchronous programming (AsyncIO, async FastAPI endpoints), microservices architecture, scripting & automation, data processing pipelines, exception handling & structured logging, API performance tuning & concurrency handling, performance optimization, debugging

● Databases: PostgreSQL, MySQL, SQLAlchemy (ORM, query optimization)

● Data & Analytics: Pandas, NumPy, data validation frameworks, ETL workflows

● Cloud Platforms: Azure (App Services, Azure exposure), GCP (Cloud Run, Vertex AI – exposure)

● DevOps & Tools: Docker, virtual environments & dependency management (pip, venv), GitHub Actions, CI/CD pipelines, Git, JIRA, VS Code

● Testing: Unit & integration testing with PyTest, API testing with Postman

● AI (Supporting): OpenAI API, HuggingFace (used selectively for automation and NLP tasks) PROFESSIONAL EXPERIENCE

Randstad Technologies Feb 2025 - Present

Python Developer

● Designed and maintained FastAPI-based Python microservices supporting 5+ internal teams in production.

● Built robust data processing pipelines with Pandas and NumPy to cleanse, validate, and transform structured and semi-structured data, processing 1M+ records per cycle with strict quality checks.

● Developed RESTful APIs for internal tools, improving system integration and reducing manual operational effort across teams.

● Implemented caching, logging, and exception-handling mechanisms to improve API reliability and reduce average response times by 30%.

● Containerized Python services using Docker and automated deployments through GitHub Actions CI/CD pipelines, cutting deployment time by 25% across development and testing environments.

● Integrated lightweight AI/NLP features (text classification, summarization) using pre-trained models to enhance automation use cases. Randstad Technologies Jul 2024 - Jan 2025

Python Developer Intern

● Supported development of Python-based automation scripts for data analysis, reporting, and internal workflows, reducing manual effort by 5–8 hours per week for operational teams.

● Assisted in building and testing REST APIs using FastAPI and Flask for backend services, supporting 3–4 internal tools and services.

● Implemented data cleaning and transformation logic using Pandas, improving consistency across 8–10 recurring datasets.

● Contributed to proof-of-concept NLP features using OpenAI API to automate summaries and responses, piloted by 2 internal teams.

● Collaborated with senior developers to debug issues, write unit tests, and improve code quality across 10+ feature updates. KPMG Jul 2021 – Aug 2022

Python Developer

● Architected end-to-end Python automation pipelines for financial and audit datasets, reducing manual review effort by 150+ hours per quarter across multiple engagements.

● Developed reusable Python modules for data validation, anomaly detection, logging, and reporting across 20+ workflows in production environments for internal data platforms.

● Designed and deployed FastAPI and Flask services to expose data processing logic as secure APIs for internal stakeholders and analytics teams.

● Optimized SQL queries and integrated Python services with relational databases using SQLAlchemy for improved query performance.

● Collaborated with 5–7 cross-functional teams to deploy Python applications on Azure and GCP, supporting 10+ services across development and production environments with consistent uptime.

● Applied rule-based and statistical techniques to support risk scoring and exception detection in 2–3 pilot use cases, enabling early identification of high-risk transactions and data anomalies.

● Built Python scripts using Pandas and NumPy to clean, transform, and validate 500K–1M+ records per cycle for analytics and reporting workflows in production environments.

● Developed RESTful APIs to integrate 6–8 internal tools, improving data accessibility for 20+ business and analytics users across teams.

● Assisted in implementing automation logic for reporting and data quality checks across 5+ client and internal engagements, reducing repetitive manual validation tasks.

● Supported code reviews, documentation, and deployment processes across 10–15 feature releases, improving development efficiency and long-term codebase maintainability.

PROJECTS

● Fraud Detection System – Formulated a Flask-based API using rule-based logic and statistical scoring to enable real-time transaction risk assessment and automated fraud alerting.

● Memories App – Constructed a full-stack React + Flask application with JWT authentication, AWS S3 media storage, and secure CRUD operations for managing user posts.

● GenAI Project – Formulated a GenAI-driven retrieval system using LangChain and OpenAI for document querying, enhancing response accuracy, and minimizing manual review effort.

EDUCATION

Rowan University, NJ, USA Sep 2022 - May 2024

Master of Science in Computer Science

Vadodara Institute of Technology, India Aug 2017 - Jun 2021 Bachelor of Engineering in Computer Science

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