Data Engineering for Fraud Prevention - Angela Ramirez

We talked about: Angela's background Angela's role at Sam's Club The usefulness of knowing ML as a data engineer Angela's career path Transitioning from data analyst to data engineer/system designer Best practices for system design and data engineering Working with document databases Working with network-based databases Detecting fraud with a network-based database Selecting the database type to work with Neo4j vs Postgres The importance of having software engineering knowledge in data engineering Data quality check tooling The greatest challenges in data engineering Debugging and finding the root cause of a failed job What kinds of tools Angela uses on a daily basis Working with external data sources Angela's resource recommendations Links: LinkedIn: https://www.linkedin.com/in/aramirez1305/ Twitter: https://twitter.com/angelamaria__r Github: https://github.com/aramir62 Previous podcast talk: https://twitter.com/i/spaces/1OwGWwZAZDnGQ?s=20 Free ML Engineering course: http://mlzoomcamp.com Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html