Need some advice/feedback on my path to become a end-to-end Data Analyst/Engineer

[Monsieboy]

Worked as a Data Analyst for 3 years (Python, SQL, SPSS, MongoDB and a bit of AWS) and did a lot of ETL and dataviz (but not with PBI or Tableau. My Python is very good, wrote scripts with subfunctions over 1000+ lines long, so that's probably the tool I'm best at.

Unfortunately we didn't use Microsoft Azure stack, which is more used in my country than AWS.

So I'm going to learn it, especially since I learned Power BI and got the PL-300 certificate.

I want to become a "full-stack" Data Analyst: I feel like I already got the front-end down, both with my experience where I was bridging the Business and Data gap. And the Power BI course I did also was helpful, I did a 50h DataCamp hands-on course that had PBI Desktop exercises in each chapter. So it's not just the theoretical PL-300 exam that I did, which also was great.

Now I want to focus on the back-end, aka Data Engineering.

I'm getting the AZ-900 + DP-900 certificates probably this week.

My plan is to then get the DP-203 cert before it is retired.

Mainly because I think it's a baller cert to learn about Azure and a valued cert in the market, and also because it includes DataBricks and Spark, but also Python and SQL. (I know it's gonna be replaced by DP-700, but I don't think DP-700 is a real replacement)

Then after DP-203 I want to go for DP-600, because Fabric is being pushed, and also because I already did PL-300, and apparently PBI is a significant part of that cert exam, so I feel like I'll have that advantage.

After that I want to do the DP-700 Fabric Data Engineer cert which replaces the DP-203 cert.

This is like a 3 month vision.

Meanwhile I'm also applying for new job roles that are more Data Engineer and MS Azure leaned.

Do you guys think this is a solid plan?

Microsoft certs, unlike many others, are industry-recognized. But also, I feel like when you do a cert, you force yourself to learn the ins and outs of the tool and learn what's possible and the right way to use it, like it was meant to be used by the developers who created it.

[V-yubandi-msft]

Hi @Monsieboy ,

We noticed we haven't received a response from you yet, so we wanted to follow up and ensure the solution we provided addressed your issue. If you require any further assistance or have additional questions, please let us know.

Your feedback is valuable to us, and we look forward to hearing from you soon.

Thnak You.

[V-yubandi-msft]

Hi @Monsieboy ,

As we haven’t heard back from you, we wanted to kindly follow up to check if the solution we provided for your issue worked for you  or let us know if you need any further assistance?

Your feedback is important to us, Looking forward to your response. 

Thank You.

[V-yubandi-msft]

Hi @Monsieboy ,

we wanted to check in as we haven't heard back from you. Did our solution work for you? If you need any more help, please don't hesitate to ask. Your feedback is very important to us. We hope to hear from you soon.

Thank You.

[V-yubandi-msft · Accepted solution]

Hi @Monsieboy ,

Thank you for reaching out to the Microsoft Fabric community.  Your plan to transition from a Data Analyst to a full-stack Data Analyst with a focus on Data Engineering is solid and well-structured. Here are some additional suggestions to strengthen your journey.

• It involves more than just certifications. Work on personal projects, contribute to open-source initiatives, or collaborate with peers to further your knowledge in practical scenarios.

• Join Azure and data engineering communities, attend webinars, and participate in discussions to stay updated on the latest trends and open up job opportunities.

• Besides studying for certifications, explore other learning materials such as online courses, tutorials, and books related to Azure, Data Engineering, Databricks, or Spark. Some excellent course platforms include Coursera, Udemy, and LinkedIn Learning.

• The tech world is ever-changing. Regularly read blogs, follow industry influencers on social media, and subscribe to newsletters to keep up with the latest developments in Azure and data engineering.

• Engage in coding challenges on platforms like LeetCode, HackerRank, and Codewars. This will enhance your coding skills and your ability to solve real-world data engineering problems.

• Maintain a blog or a GitHub repository to document your projects, learnings, and experiences. This not only serves as a personal reference but also showcases your expertise to potential employers.

By integrating these strategies with your certification journey, you can make significant progress toward becoming a full-stack Data Analyst and Data Engineer. Best of luck with your certifications and job applications.

If my response helped resolve your query, please mark it as the Accepted Solution so others can benefit.

And if you found my answer helpful, I'd appreciate a 'Kudos'.