Product Title - Complete Interview Preparation Material for Azure Data Engineers.
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Here is a detailed list of what is provided:
SQL
- Books: 5
- Cheatsheets: 3
- Coding Q&A: 175+ solved problems
- SQL Concepts Notes
- SQL Notes: Interview-ready tips
- Theoretical Q&A: 170+
Python
- Books: 5
- Cheatsheets: 6
- Coding Q&A:
• NumPy: 40+ solved problems
• Pandas: 70+ solved problems
• 29 Python programs frequently asked in DE interviews (with solutions)
• 85 basic Python programs every DE should know (with solutions)
• Python hands-on coding notes
4. Theoretical Q&A: 32+
Pyspark
- Book: 1
- Cheatsheet: 1
- Coding Q&A: 100+ hands-on problems
- PySpark Notes: 5
- Theoretical Q&A: 156+
Data Warehousing
- 25+ in-depth Q&A covering all warehousing concepts
Data Modeling
- 25+ in-depth Q&A on modeling
Linux for Data Engineers
- 100 most commonly used commands tailored for DE roles
GIT for Data Engineers
- Cheatsheets: 2
- In-depth Q&A: 62+
CI/CD for Data Engineers
- In-depth Q&A: 50+
DSA for Data Engineers
- DSA Notes
- 54 DSA Problems with solutions for data engineers
System Design for Data Engineers
- For Batch processing
- For stream processing
Microsoft Certification (DP-700) Fabric Data Engineer Associate
- Preparation Guide
- 118+ scenario-based and conceptual questions
Azure Data Factory
- ADF Cheatsheet
- ADF Functions
- ADF Notes: 5
- ADF Scenario Based Q&A: 50+
- ADF Theoretical Q&A: 220+
Databricks
- Books: 1
- Notes: 2
- Scenario Based Q&A: 80+
- Theoretical Q&A: 160+
Azure Synapse Analytics
- Notes: 2
- Scenario Based Q&A: 50+
- Theoretical Q&A: 150+
Azure Data Lake Storage
- Scenario Based Q&A: 30+
- Theoretical Q&A: 100+
Microsoft Fabric
- In detailed Q&A: 70+
- 118+ scenario-based and conceptual questions
Azure Functions
- Scenario Based Q&A: 25+
- Theoretical Q&A: 30+
Azure Logic App
- Scenario Based Q&A: 42
- Theoretical Q&A: 34
Azure Stream Analytics
- Scenario Based Q&A: 40+
- Theoretical Q&A: 75+
Azure Blob Storage
- Scenario Based Q&A: 25+
- Theoretical Q&A: 75+
Cosmos DB
- Scenario Based Q&A: 60+
- Theoretical Q&A: 55+
HDInsight
- Scenario Based Q&A: 35+
- Theoretical Q&A: 40+
18+ Azure Data Engineering Projects
- Project Explanations
- End to end pipelines Explanations
- Architecture Diagrams
- You can take a reference of these projects to build your own major project.
Additional Important Resources to make you completely job ready
- 6 Resume templates for Data Engineers
- Professional LinkedIn Profile Guide to get recruiters attention
- Professional Naukri Profile Guide to get 9-10 interview calls weekly.
- 30 In-detailed Data Engineering Interview Experiences
- Behavioral Interview Guide
- Product Sense Interview Guide
- Data Engineering Blogs by Tech Companies
- 14 Data Engineering GitHub repos
- My personal notes (Hbase, Hive, Scala, Spark, sqoop)
- Referral templates
- Azure Data Engineer roadmap with free resources.
Note: This is a documentation-based product (PDFs)
Trust me, It covers everything, literally everything you need to crack any company for a Data Engineer role.
It took me almost 6 months hard work, research and consistency to make this.
So Grab it and prepare for the Interviews!!
If you are looking for AWS Data Engineering Guide, Open this link -https://topmate.io/shubham_wadekar/1715556
I used the 18 projects as inspiration to build my own project. It made it super easy to explain my work confidently in interviews.
This Azure Data Engineering kit has literally everything I needed in one place. It saved me so much time and made interview prep more easy!
Shubham has covered SQL, Python, PySpark, Data Warehousing, and Data Modeling so well. The cheatsheets and solved problems made revision quick and clear
I'm preparing for Azure Data Engineer roles, and the coverage of ADF, Databricks, Synapse, and Fabric is just perfect. The scenario-based Q&A feels real and helped me practice exactly like interviews.
54 DSA problems with solutions and System Design is a really helpful for PBCs