I have worked in two roles in my career, the first of which was as a Technologist at Netflix. I was part of a team that was created to fulfill the engineering needs of the Creative Assets organization. The CA org would often make requests to the Data Engineering and other engineering team, but because they often had a full backlog, it was not uncommon for them to either reject their request or fulfill their request too late so the CA org would move onto something else. My team was created to fill this gap. I worked with stakeholders to understand their workflow and with this knowledge I built solutions for them. I worked with Python, SQL, and Spark Dataframes to build ETL pipelines that moved data from our data warehouse and into third-party sources, such as Airtable and Tableau. I also created BDP Scheduler (Airflow is the industry equivalent) jobs to run jobs like these pipelines at scheduled intervals. One of my favorite things to do was familiarizing myself with the data in our data warehouse and staying up to date with the Data Engineering team's changes; this effort led to me moving a lot of data with zero reports of inaccurate or missing data and it also allowed me to focus on building new solutions to benefit stakeholders. Apart from building data pipelines, I worked on other projects like maintaining Netflix's NPFP Firebase app, adding endpoints to an API built with Django, and setting up Jenkins pipelines.

After leaving Netflix, I worked as a Backend Engineer at a Series A startup, Staircase, which is a company that uses ML to help classify mortgage documents. In my role here, I served as the technical lead and sole backend developer for the development of two MVPs that were deployed to production. The first product I developed was a content management system for managing the documentation of all Staircase services. The backend was an API composed of several Lambda functions written in Python that sat behind AWS' API Gateway, with the infrastructure deployed using the Serverless Framework. It was responsible for loading all the files sent to a Lambda function, extracting and transforming the information needed to auto-generate API documentation for a service, and storing this data to a DynamoDB table, while static files were stored in S3. This data was consumed by our front-end, which was built with TypeScript, React, and Material-UI and deployed to AWS. Correctness was important for this project since this product is where my CTO held demos for customers every Monday. The second service I built was the Setup product, which was responsible for streamlining the customer onboarding process. This product was a full-stack service, the backend took care of creating accounts for customers, deploying dependencies in the correct steps, and notifying users when their account was completed. This was written in Python and used AWS' Step Functions to orchestrate the various Staircase services. This was also an API built with the Serverless Framework. I'm particularly proud of this project because it helped not only customers create their own isolated accounts, but it also helped developers since they could now easily create their own isolated accounts and ensure that new versions of their services would work in any newly created environment.

I believe I would be a great addition to your company as your next Software Engineer. Hiring me would mean hiring someone who loves software engineering, has excelled in both positions they've held, would be a culture add, and is excited to work.

Thank you for reading.