Hey there, fellow data enthusiasts! I stumbled upon a Reddit post from a Master’s in CS student trying to land their first data engineering job within six months. I totally get it – breaking into this field can be tough. As someone who’s interested in the same path, I thought I’d share some insights and advice from those who’ve been through it.
The original poster is already taking some great steps, like learning Python, SQL, Airflow, and AWS, and reading relevant books like ‘Data Engineering with Python’ and ‘DDIA.’ They’re also working on personal ETL/ELT projects to showcase on GitHub.
But they’re wondering when to start applying, whether AWS certifications are worth it, and what really helped others get their first data engineering job. If you’re in the same boat, you might be wondering the same things.
From what I’ve gathered, here are some key takeaways:
* Start applying early, but make sure you have a solid portfolio and some real-world experience to back it up.
* AWS certifications can be beneficial, but they’re not the only factor. Focus on building a strong foundation in data engineering concepts and tools.
* What helped others get their first data engineering job? It varies, but common themes include building personal projects, contributing to open-source projects, and networking with people in the field.
* As for what not to waste time on, it’s essential to prioritize your efforts. Focus on the most critical skills and tools, and don’t get too caught up in certifications or peripheral knowledge.
If you’re trying to break into data engineering, I hope these tips and insights are helpful. Remember to stay focused, keep learning, and don’t be afraid to reach out to others in the field for advice and guidance.