I'm Naveen and currently associated with a BIG 4 company and hold a designation of Lead Azure Data Engineer. I have commendable working experience and exposure with Azure stack. With this span of 10 years into IT industry i have worked for various domains like Wealth Asset Management, Supply chain management, Retails, Logistics, Risk Assessment, Portfolios, Treasuries, Health Care, Airlines, Green Buildings that deals with data that has to curated, modelled and visualized. The training/tutoring taken by me include Azure data Engineer -[Azure Data Factory, Azure Data Bricks, Pyspark, spark sql, Azure Devops, Airflow, Microsoft Fabric, Azure Synapse Analytics] Azure Devops Engineer - [Azure Devops, Kubernetes, Docker, TerraForm, Ansible, Jenkins], Dbt cloud
Are you a person who is tired of working in outdated technologies or a person who is working in testing/ L2 support / others and wish to upscale and find good package or are you from some other background/discipline and wanted to find a job in IT with good package or you are fresher/pass out from college thinking of choosing your career?. Then this is the course for you guys!!
What you can expect from me?
1.Tutoring Azure Services stack for the role of data engineer
2.Interview Preparation
3.Projects that supports the learning
4.Supporting documents for learning
5.Placement consultation and help.
6.Resume Building
7.Realtime working projects
Why you have to choose me?
1.Gain Domain knowledge along with technical. So you will feel working comfortable while taking the requirements.
2.I will be the tutor next to the door. You can connect me any time for consultation/help/suggestions.
3.Cool tutor for all age groups.
4.Consistency is the key. I will give a road map for constantly upgrading yourself even after you land in the job.
Thank you !! Best wishes !! Have a great day
Subjects
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Azure Data Factory Beginner-Expert
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Azure DevOps Beginner-Intermediate
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Databricks PySpark Beginner-Expert
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Azure Data Engineer Beginner-Expert
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Microsoft Fabric Beginner-Expert
Experience
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Senior Consultant (Mar, 2015
–Present) at Deloitte
Fee details
₹850–1,250/hour
(US$8.95–13.16/hour)
For Individual one to one sessions i will be charging 1100 to 1250 per hour/session. How ever if they are joining in batches say min 3 and max 5 its chargeable 950 per head/per session. If candidates are willing to join in batch having count more than 5 say 7 to 10, it will be 850 per head/per session.
Courses offered
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Azure Data Engineer
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US$500
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Duration: 40 Hours
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Delivery mode: Online
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Group size: 3
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Instruction language:
English,
Tamil
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Certificate provided:
Yes
Total 40 Sessions:
15 Sessions - ADF, ADL, Azure Sql, Azure Synapse Analytics, Microsoft Fabric, one lake, Function App, Logic Apps including lab practices.
6 Sessions - Spark, Azure Data Bricks and its Features including lab practices
10 Sessions - Microsoft Fabric
7 Sessions - Pyspark And Spark Sql coding.
2 Sessions - Projects
The Pricing is based on one to one session. If people are joining in groups min 3. The price will be reduced to 400 USD.
Note: Free Demo is available for 30 mins.
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Microsoft Fabric
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US$600
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Duration: 2 Months
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Delivery mode: Online
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Group size: Individual
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Instruction language:
English
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Certificate provided:
Yes
The course will cover the below
One Lake
Short cuts
Fabric Notebooks
Power BI
Sql warehouse
Data flows
Power query
Data pipeline
Real time project
Pyspark coding
Devops practices
GIT
End to End orchestration
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Fabric Data Engineering with Gen AI
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US$800
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Duration: 2 Months
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Delivery mode: Online
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Group size: 6 - 10
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Instruction language:
English
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Certificate provided:
Yes
Most companies are still drowning in "Data Silos" and manual ETL maintenance. Meanwhile, the top 1% are moving to Microsoft Fabric + Generative AI.
We’re cutting through the noise. This isn't just about moving data; it’s about building a self-healing, AI-driven Data Factory.
What’s inside the masterclass?
OneLake Mastery: Say goodbye to data duplication forever.
Gen AI as your Architect: Use LLMs to write Spark, SQL, and auto-document your pipelines.
Zero-Movement Tech: Connect to AWS/GCP without moving a single byte.
Real Projects: Build a pipeline that fixes its own errors using AI.