Interesting Data Gigs # 72: Elevate your personal brand and a get role faster

Open positions at Netflix, Vercel, Autodesk and SurveyMonkey

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Elevate your brand ASAP and get a role faster

Hey Data Geek. Today’s topic? Build a strong personal brand and see how more job offers will come to you in the long term.

How to do that as a Data Engineer? Here I let you some tips:

  • Start by building a strong online presence through platforms like LinkedIn and GitHub, where you can share your projects, contributions, and insights

  • Actively engage in relevant communities (Data Quality Camp is one of my favorite Data-focused communities) and forums to establish yourself as a thought leader and network with professionals in the industry.

  • Additionally, create a personal website or blog (this newsletter is an example of it and it’s built with beehiiv) to share your knowledge and experiences, demonstrating your ability to solve complex data problems.

  • Collaborate on open-source projects to demonstrate your teamwork and problem-solving skills.

  • Attend industry conferences (like Trino Summit 2023) and events to stay updated with the latest trends and technologies, and consider speaking at these events to establish yourself as an expert.

  • and finally, continuously invest in your professional development by acquiring new skills and certifications, as this will enhance your credibility and make you stand out in the competitive field of data engineering.

If you make this right, I guarantee you that you won’t have to find another job, they will come to you.

Time to elevate yourself, my friend.

Who is hiring this week?

Good luck with your job application

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This book is very interesting for so many reasons. First, it’s not finished and it’s based on feedback. So, read it, write your feedback to Simon, and learn in the process.

Interesting resources of the week

Tool of the week: Amazon SageMaker HyperPod

We are excited to share that Amazon SageMaker HyperPod is now generally available to enable training foundation models with thousands of accelerators up to 40% faster by providing a highly resilient training environment while eliminating the undifferentiated heavy lifting involved in operating large-scale training clusters. With SageMaker HyperPod, machine learning (ML) practitioners can train FMs for weeks and months without disruption, and without having to deal with hardware failure issues.


Marcos out

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