At Polestar, I collaborated with a team to develop the data pipeline for the “Charging Map” application, which is showcased in Polestar Spaces (showrooms). The backend infrastructure leveraged AWS Lambdas, NodeJS, TypeScript, and GraphQL.
I was responsible for integrating data from three different external APIs into a unified, reliable dataset used to map charging stations. We implemented an ETL process to extract, transform, and load data from various sources, ensuring that the information was consolidated into a single source of truth for the application. During my time on the project, I identified a lack of testing in our data work- flows and took the initiative to establish a robust testing framework. Within my first two weeks, I introduced a set of best practices, leading a workshop to demonstrate efficient testing strategies and showing the team how to refactor code into smaller, testable components. These improvements significantly boosted the system's reliability and maintainability. In early 2022,
I was headhunted to join a new team within Polestar, tasked with developing a top-priority feature: the Polestar Referrals Program, which successfully launched in May 2022. Alongside this, our team inherited two older codebases. I played a key role in refactoring these into simpler, more testable components by breaking out business logic into React hooks, significantly improving code maintainability and reliability.
Technologies:
TypeScript, Node, AWS, Serverless, AWS Lambda, DynamoDB, GraphQL, Google Maps, Jest, React Testing Library, Webpack, StepFunctions, Data, ETL, Data Modeling, Python
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Posted Oct 22, 2024
At Polestar, I developed the data pipeline for the Charging Map app using AWS, NodeJS, and GraphQL. I improved testing and refactored code for reliability.