As a data engineer on the Recruiting Engine Analytics and Data Insights (READI) team, I help design and build Amazon’s next generation data platform (Recruiting Engine Data Library - REDL) for recruiting analytics teams.

Here are some of my highlights at this position:

• Designed and implemented REDL’s internal data lake utilizing AWS Lake Formation; module was crucial in delivering data to end customers and has since then enabled analytics teams to onboard to REDL
• Mentored a junior data engineer and helped guide his intern project to completion; project was presented to the engineering team, senior manager, and director
• Assisted and owned the design and implementation of REDL’s Airflow scheduling module; built Airflow’s main infrastructure in AWS and conceptualized REDL’s DAG designs for flavored ETL workflows
• Designed and implemented REDL’s ingestion engine which pulls data from Amazon’s internal data lake into REDL accounts for further processing
• Designed and implemented REDL’s main infrastructure using AWS CDK; REDL infrastructure is built entirely in native AWS and supports modules ranging from ingestion engines to the Airflow scheduling component
• Profiled both legacy and undocumented recruiting datasets within Amazon; profiling enabled the design phase of analytical datasets

As a software developer on the Data Science Engineering team, I apply software engineering fundamentals on data science initiatives. I work on Auto-ML and data pipelines.

Here are some of my highlights at this position:

• Designed and developed a dynamic metrics generator that evaluates efficacy of machine learning models running through the auto-ML pipeline; estimated to be the highest value component of the data science engineering team
• Conceptualized the POC Java implementation of unique identifier keys among customer groups, boosting data lineage capabilities for all models running through the Auto-ML pipeline
• Campaigned internal customer interaction by heading E2E efforts with downstream development teams and acted as head liaison between the team and data scientists

As a software developer hired within the New Employee Recruitment and Development program (NERD), I utilized skills learned in college and applied them in an industry setting.

Here are some of my highlights at this position:

• Led a group of associate engineers to design and develop a CLI application which enables an OS sandbox on Windows and teaches users how to use bash; currently used by data scientists entering software development space
• Facilitated lectures on big data analytics and data engineering for new NERDs; received internal recognition for technological sessions
• Attained two certifications: MTA - Introduction to Programming in Java and Professional Scrum Developer