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_podcast/s08e06-recruiting-data-engineers.md

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@@ -41,7 +41,6 @@ topics:
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- career growth
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transcript:
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- header: Episode Opening & Guest Welcome
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- header: Episode Opening & Guest Welcome
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- line: This week, we'll talk about recruiting data engineers. We have a special guest
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today Nicolas. Nicolas is a technical recruiter who is hiring for a wide variety
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of engineering and AI roles. He worked for many years as an in-house recruiter
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time: '1:12'
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who: Nicolas
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- header: Guest Background and Career Path
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- header: Guest Background and Career Path
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- line: Before we go into our main topic of recruiting data engineers, let's start
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with your background. Can you tell us about your career journey so far?
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sec: 75
@@ -86,7 +84,6 @@ transcript:
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time: '3:10'
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who: Alexey
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- header: Onfido Role & European Hiring Footprint
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- header: Onfido Role & European Hiring Footprint
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- line: We have the UK. Then we are hiring in France, Portugal, Netherlands and Germany.
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Maybe more soon, we hope.
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sec: 192
@@ -99,7 +96,6 @@ transcript:
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time: '3:26'
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who: Alexey
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- header: 'Roles Recruited: Data, ML & Research Spectrum'
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- header: 'Roles Recruited: Data, ML & Research Spectrum'
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- line: Yeah. For now, we are hiring for mostly I would say, intermediate to senior
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levels in terms of profiles. Literally I have a bit of everything. I do hire backend,
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frontends, I do DevOps, I do security engineering, I do research. I also work
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time: '3:40'
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who: Nicolas
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- header: European Tech Market Differences
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- header: European Tech Market Differences
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- line: You mentioned that you are looking for candidates in four countries – the
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UK, France, Portugal and Germany. I'm wondering how different are the candidates
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that you find in these countries and processes? Is it the same or different? Did
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time: '6:02'
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who: Alexey
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- header: Borderless Recruitment and Competition Dynamics
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- header: Borderless Recruitment and Competition Dynamics
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- line: Yeah, but it depends. Because now you have companies hiring across different
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countries, you have less and less borders, especially in Europe. In the end, for
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example, when you hire within the EU, whether you hire for example, in Germany,
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time: '6:15'
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who: Nicolas
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- header: 'Episode Focus: Why Data Engineering Matters Now'
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- header: 'Episode Focus: Why Data Engineering Matters Now'
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- line: Okay. Interesting. Actually, the reason I reached out to you a couple of weeks
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- line: 'Okay. Interesting. Actually, the reason I reached out to you a couple of weeks
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ago and invited you to this podcast is because we had a different podcast episode
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that was about hiring data professionals – where we talked to Alicia, who was
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a guest here – but we mostly talked about data scientists. Then some people reached
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out to me saying, Hey, that was a cool episode, but we want to hear more about
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data engineers." So here we go.
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out to me saying, "Hey, that was a cool episode, but we want to hear more about
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data engineers." So here we go.'
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sec: 419
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time: '6:59'
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who: Alexey
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time: '7:48'
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who: Nicolas
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- header: Data Science Misconceptions and Data Quality Dependence
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- header: Data Science Misconceptions and Data Quality Dependence
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- line: I think data science was quite commonly romanticized like, “This is the perfect
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- line: I think data science was quite commonly romanticized like, "This is the perfect
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job where all you do is machine learning.”
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sec: 666
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time: '11:06'
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time: '12:27'
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who: Nicolas
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- header: Rising Demand for Data Engineering and Modern Tooling
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- header: Rising Demand for Data Engineering and Modern Tooling
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- line: Have you observed a spike of interest in data engineering roles recently?
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I am judging from the blog posts that I see on the internet. For a year, maybe
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a bit longer, I've seen posts on Hacker News, and in general, Reddit and on social
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time: '13:50'
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who: Nicolas
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- header: 'Recruiter Technical Literacy: Big-Picture Knowledge'
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- header: 'Recruiter Technical Literacy: Big-Picture Knowledge'
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- line: I'm wondering, as a recruiter who recruits for data engineering roles, and
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in general, for technical roles – how much of this stuff do you need to know?
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You seem to know quite a lot already, because we're talking about quite technical
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time: '16:37'
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who: Nicolas
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- header: 'Hiring Challenges: Titles, Experience Mismatch, Demand'
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- header: 'Hiring Challenges: Titles, Experience Mismatch, Demand'
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- line: In your opinion, what are the main difficulties? What are the main challenges
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of hiring data engineers?
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sec: 1127
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time: '18:56'
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who: Nicolas
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- header: Evaluating Transferable Experience from Software/BI Roles
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- header: Evaluating Transferable Experience from Software/BI Roles
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- line: I imagine that you get a bunch of applications – or you reach out to a bunch
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of people – who do not yet have the title of data engineer in their portfolio,
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like a data scientist, BI engineer, software engineer. It seems like they're doing
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time: '21:26'
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who: Nicolas
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- header: 'Expectations by Level: Junior → Senior Responsibilities'
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- header: 'Expectations by Level: Junior → Senior Responsibilities'
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- line: Do you think there are a lot of differences between hiring junior data engineers,
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middle level data engineers, and senior engineers? [cross-talk]
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sec: 1375
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time: '25:53'
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who: Alexey
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- header: Typical Interview Process and Level-Based Assessments
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- header: Typical Interview Process and Level-Based Assessments
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- line: Yeah. So the goal in the recruitment process – you have a framework. The process
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is the same but, of course, you do not expect the same whether you're talking
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to a junior or a senior engineer. For junior candidates, yes. What I've seen in
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time: '26:38'
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who: Nicolas
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- header: 'Career Switchers: Internships, Projects, and Focused Skills'
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- header: 'Career Switchers: Internships, Projects, and Focused Skills'
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- line: There is a related question. We talked about different levels – talking about
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people who are switching to data engineering. What do you look for in these people?
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I think you did mention one thing – for people who are just starting their career
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time: '30:39'
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who: Alexey
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- header: 'Resume Essentials: SQL, Python, Problems & Outcomes'
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- header: 'Resume Essentials: SQL, Python, Problems & Outcomes'
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- line: Yeah, exactly. There’s several things. First, I would say that it helps a
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- line: Yeah, exactly. There's several things. First, I would say that it helps a
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lot if you have done internships, for example. That's a good way to start. Now,
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there are a lot of online trainings coming up in resumes, whether it's on their
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own, with different technologies – the basics and data engineering use cases.
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time: '31:16'
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who: Nicolas
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- header: 'Transition Strategy: Team Structure and Role Selection'
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- header: 'Transition Strategy: Team Structure and Role Selection'
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- line: Yeah, so speaking of titles, you just mentioned that you don't really care
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about them. But I imagine that right now, many data scientists, many software
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engineers, BI engineers, data analysts, see this interest in data engineering
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time: '36:01'
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who: Nicolas
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- header: 'Cloud Fundamentals: Tool-Agnostic Conceptual Knowledge'
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- header: 'Cloud Fundamentals: Tool-Agnostic Conceptual Knowledge'
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- line: How important is it for data engineers to know cloud tools like AWS, Google
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Cloud Platform, and others? Most of the jobs, at least from what I see in Berlin,
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require that to some extent. For the rest of Europe, is that also what you see?
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time: '40:06'
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who: Nicolas
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- header: 'Infrastructure & DevOps Skills: When They Matter'
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- header: 'Infrastructure & DevOps Skills: When They Matter'
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- line: Then the question goes on, "How important is it to know infrastructure tools?"
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By this, I think they mean tools like Kubernetes or setting up databases, or whatever
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we use for data pipelines, like Kubernetes, Terraform. Is it something you also
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time: '43:57'
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who: Nicolas
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- header: 'Interview Prep: Research Company and Explain Projects Clearly'
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- header: 'Interview Prep: Research Company and Explain Projects Clearly'
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- line: Yeah. Another question, "What would you recommend that job applicants do before
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talking to a recruiter or a hiring manager?"
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sec: 2675
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time: '47:43'
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who: Alexey
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- header: Targeted Applications vs. Spray-and-Pray Approach
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- header: Targeted Applications vs. Spray-and-Pray Approach
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- line: Exactly. I always ask this question. [laughs] I always ask, "What do you know
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about the company? Just tell me everything that you know, and if there's something
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that is not true. Then I will complete the gap and give you more details.” Because
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time: '49:37'
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who: Nicolas
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- header: 'Hiring Without Degrees: Skills, Projects, Continuous Learning'
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- header: 'Hiring Without Degrees: Skills, Projects, Continuous Learning'
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- line: What would you say about people without a formal computer science degree?
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Would you hire somebody without a formal degree, but someone that has a set of
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data engineering projects?
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time: '53:19'
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who: Nicolas
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- header: 'Standout Project Examples: First Pipelines & Privacy Work'
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- header: 'Standout Project Examples: First Pipelines & Privacy Work'
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- line: So, you mentioned projects like 10 times by now. Do you maybe remember some
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of the projects that really stood out, where you thought "Wow! Cool! This candidate
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is definitely passing my screen into the next step."
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time: '54:41'
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who: Nicolas
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- header: 'Portfolio & GitHub: Shareable Work and Storytelling'
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- header: 'Portfolio & GitHub: Shareable Work and Storytelling'
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- line: So it's not about the portfolio. It's not about your public GitHub profile
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with all the projects you’ve worked on – it's more about what projects you can
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talk about to the recruiter and explain it concisely in a way that any non-technical
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time: '56:22'
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who: Nicolas
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- header: 'Industry Fit: Domain Knowledge for Regulated Data'
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- header: 'Industry Fit: Domain Knowledge for Regulated Data'
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- line: There is a question from Dan. The question is about switching from one industry
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to another. I'm wondering, do you actually look at the industry where the candidate
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works in? Or do you care mostly about "Okay, this person is already a data engineer
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time: '59:59'
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who: Nicolas
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- header: 'Follow-up Resources: Webinars and Further Reading'
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- header: 'Follow-up Resources: Webinars and Further Reading'
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- line: '[laughs] I’m the one who should be doing this. So thanks a lot for doing
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- line: '[laughs] I''m the one who should be doing this. So thanks a lot for doing
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that.'
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sec: 3659
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time: '1:00:59'
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time: '1:01:34'
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who: Nicolas
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- header: Episode Close and Final Tips
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- header: Episode Close and Final Tips
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- line: Yeah, for everyone who is going to have Easter holidays – enjoy your holidays.
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Yeah, it was nice talking to you. Thanks, everyone for tuning in, for asking questions.
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That was amazing. Have a great rest of your day.
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- name: Episode Close and Final Tips
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startOffset: 3698
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url: https://www.youtube.com/watch?v=hylxiu4VGTo&t=3698
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endOffset: 3665
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endOffset: 3712
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---
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Links:
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