Interview with an Amazon BI Engineer
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- čas přidán 1. 08. 2024
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====== ✅ Details ======
🤔 Ever wondered what it's like to work at Amazon as a BI engineer?
Dan, an ex-Google data scientist, interviews Hank Lo, a BI engineer at Amazon ( / chun-wei-lo . They discuss various topics including the BI engineer role at Amazon, project experience, interview experience, Amazon's leadership principles, and interview prep strategy. Make sure to check out datainterview.com/ for more content!
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====== ⏱️ Timestamps ======
0:00 Intro
00:52 Hank's Career Story
03:31 Project Experience at Amazon
11:55 BI Engineer Interview Experience
13:52 Amazon's Leadership Principles
20:40 Interview Prep Tips
====== 📚 Other Useful Contents ======
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2. How to Crack the Data Scientist Case Interview
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3. How to Crack the Amazon Data Scientist Interview
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====== Connect ======
📗 LinkedIn - / danleedata
📘 Medium - / datainterview - Věda a technologie
Appreciate this !
Good content, thank you.
Is this the same guy in your Amazon BI Engineer mock interview video?
look like it
What’s the difference between a BI engineer and a BI analyst?
I'll try to answer that as somebody who's been in BI at tech companies for ~10 years:
BI is generally focussed on collecting business data for insights and performance measurement, and the two roles can be split into "collecting business data" and "insights and performance management". BI engineers create data sources by pushing code and/or using a tool for scheduling "data pipelines" (if I had to summarize what BI/data engineers did in three words, it would be "build data pipelines" or "build data warehouses"). BI analysts make dashboards using those data sources in tools like Tableau, Power BI, etc. Both roles use a lot of SQL and perform a lot of data manipulation/transformation. While BI analysts are sometimes better than the engineers at SQL, the engineers are almost always better at a scripting language like Python. Analysts typically make a lot of "solo" work like dashboards and business analyses, and engineers push code to a common shared repository and know how to collaborate with Git, ticketing systems, code reviews, etc. Engineers usually wish they had more time to make pretty charts and dashboards and understand their strategic impact, while the analysts wish they had more time to learn the latest modeling techniques in their favorite scripting language (and to spend more time in that language). Engineers are paid more, too - sometimes as much as 50% more (like $100K vs $150K) - and that's due to the demand for people who are expert in scripting languages. The career trajectory for BI analysts is either to stay in BI and move into management, or to move into finance (esp. FP&A), data science (if they learn scripting and statistics), business operations, or business strategy (both of which are like FP&A but with less time spent arguing over which managers to give more budget). I haven't seen any BI analysts become data engineers, but I'm sure it happens. There are also roles within companies that are hybrid BI/finance/data science that focus more on creating predictive models of revenue, and while those positions are a little more rare, that's the role I took (and it sounds like Dan has also been in those roles, too).
@@thuggfrogg thank you for your time and analogy. Trying to figure out which one to choose.
You should simply tell what to prepare and what not to prepare for a bie interview rather than having all this discussion.