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Exdol Davy

Amazon, FireTV Digital Media Catalog

Here is more information on my experience with Amazon, FireTV on the Digital Media Catalog team

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Summer 2021 Internship Project Overview

As part of the Amazon Propel Program (APP) Internship, I spent 12 weeks at Amazon; 2 of which were part of a hands-on Software Development Engineer Bootcamp where I learned about the essentials of the internal frameworks in Amazon such as brazil workspaces, dependency management, unit testing, git, code reviews, code deployment pipelines, and scrum.

I built a Data Ingestion pipeline for FireTV to ingest catalog data across internal Amazon Prime Video and over 100+ other content providers, utilized the aforementioned ingestion pipeline to provide monitoring of failures across the various systems it interacted with to maintain SLAs, and created a framework for my team to migrate an internal tool to use new AWS software, reducing overhead from an older internal Amazon technology.

Tools Used

AWS
Block Diagrams
Git
IntelliJ
Java
JavaScript
Jira
Linux
Microsoft Powerpoint
MySQL
Nice DCV
Node.js
Query Logs
Slack
Unit Testing

Summer 2022 Internship Project Overview

Upon my return as a Software Development Engineer Intern, I was tasked with creating an AWS home for my team's field-wise aggregate metrics dashboard. This was an internal tool that could display metadata for structures and field demographics of all FireTV's VOD JSON data.

I created an additional view in the current internal dashboard tool for a new category of data in my team's database and kickstarted a distributed job to calculate the metadata for these JSON files specifically by way of an Apache Spark EMR cluster. Additionally, I fixed a 2‑month blocked internal code deployment pipeline that was failing prior to my internship start date. Finally, I utilized Java and several AWS services to transition data into a front-end view on Amazon QuickSight.

One especially challenging obstacle was transforming data for appropriate ingestion, as there exists hundreds of files containing metadata, each with hundreds, if not thousands, of fields present; however they all needed to be ingested uniformly by Amazon Athena. I recieved experience in creatively solving this problem when no other developers on my team knew how.

Tools Used

Amazon Athena
Amazon CloudWatch
Amazon EMR
Amazon QuickSight
Amazon S3
Distributed Job Scheduling
Git
IntelliJ
Java
Jira
JavaRDD
JSON
Linux
ObjectMapper
Slack
Unit Testing

Bonus

Overall, I've had an amazing experience working with FireTV, learned from amazing senior software developers, and met so many great colleagues.

Ingestion Plan For Amazon Athena