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Additional Posts in Data engineers India
Hi fishes,
Need your opinion.
Working for Wipro as azure data engineer in Spark, Hive, Azure ADF, ADB etc.
Current CTC: 17.5 LPA
Total YOE: 11 years
Relevant exp in big data: 6 yrs
Relevant exp in Azure: 2+ yrs
Got offer from Atos of 26.4 LPA. Is this a good offer? or Shall I search other job at 30+ LPA?
Getting calls from some product companies like JPMorgan Chase Chubb. How much can I expect from these product companies?
Wipro Infosys Tata Consultancy IBM Capgemini Cognizant Accenture India
McKinsey & Company Hi guys,
Please help me with the referral.
Senior/Lead data Engineer
Exp -- 8.5 years
Notice period -- 30 days
Tech stack -- Big data,Hadoop, Spark, Kafka, Azure,Python,Scala,Sql
Please ping your email id .I will share the Cisco" class="linkified" target="_blank" rel="nofollow" >resume.Cisco Target Bosch Intuit Amazon McKinsey & Company Indeed Flipkart JPMorgan Chase Morgan Stanley VMware Intel Corporation Hewlett Packard Enterprise Paypal Salesforce
I am working as data engineer at Accenture with 2 YOE with ctc of 11LPA. After clearing all the technical rounds at Impetus technologies, tomorrow I have my HR discussion. She told she can't give more than 16 LPA. What should i do? How much should i ask? I am expecting somewhere around 19-20 LPA. Can anyone pls help. Accenture Impetus technologies inc
Hello All, In the next couple of months i am targeting companies like Apple , American express, Salesforce, Microsoft etc. Can anyone please share the required skill set and preparation strategy for these companies? YoE - 4 years Current skill set - Advanced SQL , Pyspark,Azure services, Hadoop ecosystem , shell scripting, Power BI
I am not very good at DSA.
Apple Microsoft Salesforce Amazon
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I am an Azure DE, here are the things that I observed during my interviews
1. SQL & PySpark - Practice questions on sql joins, window functions, and know how to write same query in Pyspark.
2. Scenario based questions:
My data pipeline has failed, what necessary actions you take
How do you optimize the performance
Build a sample data pipeline for the usecase, and give justification for each and every step.
3. Data warehousing concepts -
Schemas in dwh, scd and its types, incremental load and full load
4. Architectural and design questions - Spark Architecture, Medallion Architecture
5. Have a strong grip on the data engineer project you're doing (can be the one which you're working or your personal one), explain in and out and know the specification of each tool.
Keep trying, all the best!! You're almost there. Don't lose hope
Checkout youtube lot of resources
How about python questions?