DataTalks.Club

Data Engineering for Fraud Prevention - Angela Ramirez

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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

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