
Prateek | AI • Data • Tech
@techwithprateek

I was a backend engineer. Then I joined Microsoft as a Data Engineer Here’s exactly how I made the switch 👇 Nobody told me there was a “right” way to do it. So I just started First, I picked up Python Not because someone told me to, because data runs on it. I built small internal tools, prototype apps, anything to get my hands dirty. Then I went deeper Distributed systems. Because if you don’t understand how data moves across machines, you’ll always be guessing. I explored Hadoop, understood MapReduce, then went all in on Spark, the real king of data processing. I studied its internals, wrote PySpark scripts, used Kaggle datasets just to practice. Then came Airflow for orchestration. Then data visualisation. One thing at a time. No bootcamp. No fancy degree pivot. Just consistent, intentional learning, while working a full-time job. It took time. But 5+ years into data engineering now, I can say it was worth every confusing night spent debugging a Spark job 😅 If you’re a backend dev, a software engineer, or just someone stuck in a role that no longer excites You don’t need permission to switch You just need a plan. 💾 Save this for when you feel stuck in your current role 💬 Comment “switch” and I’ll share my roadmap in detail with resources 🔁 Follow to keep your transition clear and direction steady
Likes
Gráfico
Patrocinado
Performance
1,632
Current Likes
—
Since Page Load
+0
Per Minute
+0
Per Hour
15.29%
Engagement Rate
173.53%
Comment Rate
Performance monitor
Next Likes Milestone
63.20%
0
0
0
0
Detalles del post
Texto
I was a backend engineer. Then I joined Microsoft as a Data Engineer Here’s exactly how I made the switch 👇 Nobody told me there was a “right” way to do it. So I just started First, I picked up Python Not because someone told me to, because data runs on it. I built small internal tools, prototype apps, anything to get my hands dirty. Then I went deeper Distributed systems. Because if you don’t understand how data moves across machines, you’ll always be guessing. I explored Hadoop, understood MapReduce, then went all in on Spark, the real king of data processing. I studied its internals, wrote PySpark scripts, used Kaggle datasets just to practice. Then came Airflow for orchestration. Then data visualisation. One thing at a time. No bootcamp. No fancy degree pivot. Just consistent, intentional learning, while working a full-time job. It took time. But 5+ years into data engineering now, I can say it was worth every confusing night spent debugging a Spark job 😅 If you’re a backend dev, a software engineer, or just someone stuck in a role that no longer excites You don’t need permission to switch You just need a plan. 💾 Save this for when you feel stuck in your current role 💬 Comment “switch” and I’ll share my roadmap in detail with resources 🔁 Follow to keep your transition clear and direction steady
Publicado
April 17, 2026, 02:33 PM
Dimensiones
720 × 1280
ID del post
3877351772206017433
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