Career Switch to Data Engineer

Switching from Automation Testing to Data Engineering is a great move, especially with your experience in automation. The job market for Azure Data Engineers is strong, as cloud-based data solutions are in high demand across industries.

Job Market Outlook
-Service-based companies (TCS, Infosys, Cognizant, etc.) focus on broad data pipeline development and cloud integration. They usually have structured hiring processes.
-Product-based companies (Microsoft, Amazon, Flipkart, etc.) look for deeper expertise in data modeling, real-time processing, and optimization. They have tougher technical rounds but offer better pay and growth.

How to Prepare for the Transition?

1. Learn Azure Fundamentals: Get familiar with Azure Data Factory, Azure Synapse, Azure Databricks, and Azure SQL.
2. Master Data Engineering Concepts: Focus on ETL, data pipelines, SQL, Python, Spark, and cloud architecture.
3. Hands-on Projects: Build and deploy end-to-end data pipelines on Azure using real-world datasets.
4. Mock Interviews & DSA Practice: Service-based companies emphasize SQL & scenario-based questions, while product-based firms focus on DSA, system design, and big data concepts.

I highly recommend joining the iSkills by iQuanta WhatsApp group: https://chat.whatsapp.com/B6weknl7133BQXjPva0pgB

It has structured courses, live mentorship, and exclusive resources tailored for Data Engineering aspirants. You can interact with industry experts, get resume guidance, and access mock interviews to boost your chances of cracking top companies. I found the discussions and study materials there incredibly helpful while exploring career transitions.

Are you excellent in SQL and Python. And are you willing to upskill to ML and AI. If both yes, proceed. Else take a step back and think again.