Pareshkumar Mahyavanshi
Software Developer at Pythonwise Inc @Prealize Health
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WORK HISTORY
Software Developer at Pythonwise Inc @Prealize Health
Palo Alto, CA, US
Develop and maintain production pipelines using AWS services (IAM, EC2, S3, Lambda, SNS, SQS, CloudWatch), integrating with Docker, Terraform, and Kubernetes for robust infrastructure management- Process incremental and historical data batches through Jenkins, Airflow, Databricks, and GitLab, supporting predictive healthcare analytics- Design and implement secure SFTP automation for encrypted and compressed file transfers, maintaining high-security standards for sensitive data handling- Develop end-to-end automation solutions utilizing Python, R, SQL, and Shell scripting. Manage configuration files, including TEXT, JSON, CSV, YAML, and Jinja templates, to streamline CI/CD processes- Utilize Docker and Terraform on platforms like Jenkins, Airflow, and Databricks, with GitLab for CI/CD to automate and streamline the software lifecycle on AWS- Implement code testing with SonarQube integrated into GitLab to automate code quality checks, enhancing code compliance and overall project quality- Customize data processing pipelines for new client onboarding according to specific requirements and ensure seamless integration- Maintain and update infrastructure and orchestration setups to handle varying demands and leverage new technology features- Collaborate with teams across Data Engineering, Data Science, Clinical, Application, and Analytics departments, and work with client representatives to integrate and automate the entire data pipeline, ensuring efficient operations and meeting client requirements- Experience building application governed under HIPAA, PHI and PII compliance requirements
EDUCATION
Veer Narmad South Gujarat University, Surat
Bachelor's degree
Harrisburg University of Science and Technology
Master's degree
San Francisco Bay University
Master of Science - MS
ABOUT PARESHKUMAR MAHYAVANSHI
I design and automate scalable, secure backend systems and cloud-native infrastructure. My core expertise includes Python development, AWS services, and DevOps practices that improve deployment, observability, and data pipeline automation. I automate cloud environments using Terraform, AWS CDK, and CloudFormation, and implement CI/CD pipelines using Jenkins, GitLab, and Apache Airflow. I use Docker and Kubernetes not only for container orchestration but also to manage workflow scheduling, monitoring, and resource allocation in production-like environments. I’ve built fully automated, end-to-end data pipelines involving secure file processing via SFTP, integrated with Airflow, Lambda, and AWS services for event-driven execution and delivery. My work includes building monitoring and alerting systems using AWS CloudWatch, Databricks logs, and custom metrics. I manage multi-environment configurations using Ansible and deploy Kubernetes workloads. Separately, I’ve built full-stack web applications using Flask and Django for internal projects, with PostgreSQL and MongoDB as backend data stores. These solutions supported operational workflows, internal dashboards, and task automation. I focus on solving complex infrastructure and automation challenges through secure, reliable, and maintainable systems. Career Highlights: Delivered automated cloud-based pipelines using Jenkins, Airflow, GitLab CI, Databricks, and AWS Built encrypted file workflows using Python, Bash, and sFTP integrated with Lambda and Airflow Developed monitoring and alerting with CloudWatch, Databricks logs, and custom metrics Provisioned infrastructure using Terraform, CloudFormation, and AWS CDK Managed Kubernetes resources with Helm for both orchestration and workflow execution Built internal full-stack applications using Flask and Django with integrated PostgreSQL and MongoDB Streamlined multi-environment provisioning using Ansible Technical Skills: Languages: Python, Shell scripting (Bash), R, SQL Cloud Platforms: AWS (EC2, S3, IAM, RDS, Lambda, SFTP, SNS, SQS) IaC & Automation: Terraform, AWS CDK, CloudFormation, Ansible CI/CD & Pipelines: Jenkins, GitLab CI, Apache Airflow, Databricks Frameworks: Flask, Django Databases: PostgreSQL, MongoDB, SQLite Containers & Orchestration: Docker, Kubernetes, Helm Monitoring & Logging: CloudWatch, Databricks, Docker logs Tools: Jira, Confluence, SharePoint, PyCharm, VS Code
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