- Develop new content for Amazon OpenSearch Service, including documenting new features, writing sample code in Python and JavaScript, creating tutorials and flow diagrams, updating procedures and best practices, and testing APIs- While on the Amazon EMR doc team, designed and wrote the EMR Serverless User Guide and API Reference from scratch, while also adding features and improving readability for EMR on EC2ʼs Management Guide, Release Guide, and API Reference- Wrote Python scripts to automate XML content for the EMR Release Guide, including application version information tables and content for each release version detail page, using content from the engineering team’s release manifest repository- Collaborate with PMs and engineers to understand customer needs, refine user experience, and keep existing docs accurate- Work with UX designers to write copy for features on the AWS OpenSearch and EMR consoles and provide design feedback- Support the internal AWS community with training videos, blogging, mentoring, campaign participation, and customer calls- Collaborate with the open-source OpenSearch documentation team to ensure that the Amazon OpenSearch Service guide (https://docs.aws.amazon.com/opensearch-service/latest/developerguide/what-is.html) presents features in a manner that’s consistent and harmonious with the open-source guide (https://opensearch.org/docs/latest)

- Helped SaaS companies connect with their technical customers by writing developer-focused content (with a focus on TDD, C++, Python, Big Data, Node, and Machine Learning) that’s engaging and easy to understand, even for non-technical readers- Sample articles and blog posts include 'How to build a responsive image gallery in React', 'React: an Introduction', 'How to create partial functions in Python', 'Using datasets with computer vision', and 'Dynamic image resizing with Serverless'

- Built customized data pipelines using Python to assemble data from multiple internal sources, transforming these datasets into user-friendly data trackers for various teams with the view of supporting interactive analytics and day-to-day operations- Created SQL queries with Presto to aggregate distributed data from Netflix’s Big Data portal and fetch additional data using GraphQL and REST API endpoints from proprietary Netflix applications- Used schemas to create Iceberg tables in Netflix’s Big Data portal to preserve data integrity from manual-input tooling- In partnership with internal stakeholders, iterated upon Java applications for end-users to better streamline workflow - Integrated customized webhooks with Node.js to automate real-time data across Airtables, based on event triggers- Developed quick turnaround solutions to optimize existing datasets, such as adding high confidentiality indicators in working solutions with a daily scheduled Python job

- Engineered React/Redux and Node.js/Express Docker-containerized SPA, deployed on AWS Elastic Beanstalk with RDS Postgres to contain event-based transactions in a uniform ecosystem by refactoring logic that relied on third-party services- Configured customized Node.js server to manage end-user requests with modularized middleware and asynchronous database connections, orchestrating effective data transfer between client requests and a Copper API- Leveraged YAML files to dynamically parse data and render content, creating a smooth workflow for a non-tech team- Implemented Node.js/Express middleware within an online learning platform codebase to refactor notification system