3 Matching Annotations
  1. Nov 2020
    1. In-depth questionsThe following interview questions enable the hiring manager to gain a comprehensive understanding of your competencies and assess how you would respond to issues that may arise at work:What are the most important skills for a data engineer to have?What data engineering platforms and software are you familiar with?Which computer languages can you use fluently?Do you tend to focus on pipelines, databases or both?How do you create reliable data pipelines?Tell us about a distributed system you've built. How did you engineer it?Tell us about a time you found a new use case for an existing database. How did your discovery impact the company positively?Do you have any experience with data modeling?What common data engineering maxim do you disagree with?Do you have a data engineering philosophy?What is a data-first mindset?How do you handle conflict with coworkers? Can you give us an example?Can you recall a time when you disagreed with your supervisor? How did you handle it?

      deeper dive into [[Data Engineer]] [[Interview Questions]]

    1. The Hierarchy of AnalyticsAmong the many advocates who pointed out the discrepancy between the grinding aspect of data science and the rosier depictions that media sometimes portrayed, I especially enjoyed Monica Rogati’s call out, in which she warned against companies who are eager to adopt AI:Think of Artificial Intelligence as the top of a pyramid of needs. Yes, self-actualization (AI) is great, but you first need food, water, and shelter (data literacy, collection, and infrastructure).This framework puts things into perspective.

      [[the hierarchy of analytics]]

  2. Oct 2018
    1. tl;dr: data engineer = software, coding, cleaning data sets data architects = structure the technology to manage data models and database admin data scientist = stats + math models business analysts = communication and domain expertise