Summary
Overview
Work History
Education
Skills
Projects
Timeline
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Challa Narayanaswamy

St. louis,MO

Summary

With over 8 years of experience as a Python Developer, I have specialized in creating scalable backend systems and robust data pipelines, primarily in the healthcare and finance sectors. I possess deep expertise in Python programming, data integration via ETL processes, and working with cloud services like AWS, Azure, and Google Cloud. My focus has been on building secure, high-performance applications that handle large datasets while ensuring compliance with industry regulations. I have a strong track record of optimizing complex systems, improving efficiency, and reducing latency. Additionally, I have worked extensively to integrate security best practices into all aspects of development, ensuring data privacy and system integrity. My ability to collaborate with cross-functional teams has helped drive innovative solutions in fast-paced, high-demand environments, making significant contributions to business success. I am adept at troubleshooting, maintaining, and enhancing existing systems, ensuring continuous improvement.

Overview

2
2
years of professional experience

Work History

Senior Quantitative Engineer / Backend Developer

VIVIO Health
Boston, USA
01.2023 - Current
  • Work closely with Quantitative Researchers, Portfolio Managers, and Product teams to design, develop, and enhance scalable backend systems for data processing and financial modeling
  • Implement advanced algorithms, optimize performance, and ensure seamless integration with analytics and trading platforms
  • Design and implement robust, scalable backend services for healthcare applications, focusing on high availability, security, and performance
  • Ensure strict compliance with HIPAA and SOC2 standards by incorporating encryption, access control, and secure data handling practices
  • Develop and deploy high-performance APIs and microservices to facilitate seamless data exchange, real-time processing, and system interoperability
  • Build and maintain portfolio optimization tools using advanced algorithms to enhance financial decision-making and risk management
  • Enhance database efficiency by fine-tuning queries, indexing strategies, and caching mechanisms to improve speed and scalability
  • Implement rigorous data validation, backup strategies, and consistency checks to ensure data integrity and reliability across MySQL, MongoDB, and MS SQL environments
  • Design, develop, and optimize large-scale data pipelines to efficiently ingest, process, and transform vast amounts of structured and unstructured market data in real time
  • Implement distributed computing frameworks, parallel processing, and fault-tolerant mechanisms to ensure high availability, data accuracy, and seamless integration with analytical and trading systems
  • Architect and implement highly reliable, mission-critical production systems designed for optimal performance, scalability, and resilience
  • Establish robust testing frameworks, proactive monitoring solutions, and automated deployment pipelines to ensure system stability, rapid issue resolution, and seamless software releases with minimal downtime
  • Leverage distributed computing frameworks like Apache Spark and Dask to efficiently process and analyze vast volumes of financial and healthcare data in parallel
  • Implement scalable data pipelines, optimize computation workflows, and utilize cluster-based processing to accelerate complex analytics, machine learning models, and real-time decision-making
  • Spearhead technical initiatives by introducing cutting-edge technologies, optimizing system architecture, and improving development workflows to enhance research and trading platforms
  • Provide mentorship and guidance to junior engineers, fostering skill development, best coding practices, and knowledge sharing, while driving innovation through the implementation of advanced algorithms, automation, and scalable infrastructure solutions

Python Developer / Quantitative Software Engineer

[Previous Employer]
  • Designed and implemented advanced Python-based quantitative research tools to analyze financial market trends, optimize trading strategies, and enhance risk management
  • Developed scalable healthcare applications to process patient data, automate clinical workflows, and improve decision-making by integrating machine learning models and real-time analytics
  • Developed scalable ETL pipelines to efficiently process and transform market and alternative datasets, ensuring high performance and flexibility
  • Integrated the pipelines with various storage solutions like cloud data lakes, relational databases, and NoSQL databases for seamless data management and access
  • Designed and optimized performance-sensitive Java applications for processing large volumes of high-frequency data with low latency
  • Focused on memory management, concurrency, and real-time processing to ensure efficient handling of time-sensitive financial and market data
  • Improved data visualization frameworks to deliver clear, actionable insights for Portfolio Managers and healthcare providers, enabling better decision-making
  • Focused on creating intuitive dashboards and interactive charts that highlight key trends and performance metrics
  • Ensured adherence to software engineering best practices by implementing version control systems like Git for managing code changes and collaboration
  • Established continuous integration (CI) pipelines using tools like Jenkins or GitLab CI to automate testing, building, and deployment, ensuring rapid and reliable software delivery
  • Fostered a culture of code quality through regular code reviews, where peers evaluate each other's code for maintainability, readability, and adherence to design standards, ultimately improving the overall software quality and reducing bugs
  • Implemented security best practices by utilizing encryption for data protection, access control mechanisms like RBAC, and secure handling of sensitive data to prevent unauthorized access
  • Applied secure coding practices, including input validation and data sanitization, to safeguard against common vulnerabilities and ensure overall system integrity

Python Developer

[Previous Company]
  • Developed data-driven applications that leverage insights from various data sources to optimize business operations and streamline decision-making processes
  • Automated workflows by integrating systems and processes, reducing manual effort and increasing overall efficiency across departments
  • Led the development of backend APIs, focusing on optimizing performance and ensuring scalability to handle high traffic and large datasets
  • Implemented efficient data processing, load balancing, and caching strategies to meet growing demands and maintain smooth system operations
  • Collaborated with the DevOps team to streamline deployment automation, ensuring faster and more reliable releases
  • Enhanced CI/CD pipelines by integrating automated testing, build processes, and deployment workflows to improve development efficiency and reduce errors
  • Conducted data analysis and validation to ensure accuracy and compliance with industry regulations
  • Worked closely with cross-functional teams, including developers, data scientists, and healthcare professionals, to design and implement cutting-edge solutions that address industry challenges
  • Focused on improving patient care, operational efficiency, and data-driven decision-making through innovative healthcare technology

Education

Master of Science - Information Technology and Management

Webster University
MO

Skills

  • Python
  • Django
  • Flask
  • FastAPI
  • NumPy
  • Pandas
  • SciPy
  • Statsmodels
  • Scikit-learn
  • Java
  • SQL
  • Bash
  • MySQL
  • PostgreSQL
  • MongoDB
  • MS SQL
  • Linux
  • Ubuntu
  • Red Hat
  • CentOS
  • Data pipelines
  • Distributed storage
  • Data warehousing
  • Spark
  • Dask
  • Kubernetes
  • Redis
  • RESTful APIs
  • GraphQL
  • API Security
  • HIPAA
  • PCI DSS
  • ISO 27001
  • NIST Standards
  • AWS
  • Docker
  • CI/CD Pipelines
  • Jira
  • Git
  • Bitbucket
  • Atlassian Suite
  • Statistics
  • Time-series Analysis
  • Portfolio Optimization
  • Market Data

Projects

Automated Risk Assessment Tool, Developed a Python-based tool to assess financial risk based on real-time market data, reducing manual workload by 70%. Real-time Data Pipeline for Healthcare Analytics, Designed and deployed a scalable ETL system to process and analyze patient records, improving data retrieval speeds by 45%. Fraud Detection System, Implemented machine learning algorithms to detect and prevent fraudulent activities in financial transactions.

Timeline

Senior Quantitative Engineer / Backend Developer

VIVIO Health
01.2023 - Current

Python Developer / Quantitative Software Engineer

[Previous Employer]

Python Developer

[Previous Company]

Master of Science - Information Technology and Management

Webster University

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Challa Narayanaswamy