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Data Engineer Job Requirements

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โ€ข1 min read
Data Engineer Job Requirements
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Naveen Pn

I am a Tech Enthusiast having 13+ years of experience in ๐ˆ๐“ as a ๐‚๐จ๐ง๐ฌ๐ฎ๐ฅ๐ญ๐š๐ง๐ญ, ๐‚๐จ๐ซ๐ฉ๐จ๐ซ๐š๐ญ๐ž ๐“๐ซ๐š๐ข๐ง๐ž๐ซ, ๐Œ๐ž๐ง๐ญ๐จ๐ซ, with 12+ years in training and mentoring in ๐’๐จ๐Ÿ๐ญ๐ฐ๐š๐ซ๐ž ๐„๐ง๐ ๐ข๐ง๐ž๐ž๐ซ๐ข๐ง๐ , ๐ƒ๐š๐ญ๐š ๐„๐ง๐ ๐ข๐ง๐ž๐ž๐ซ๐ข๐ง๐ , ๐“๐ž๐ฌ๐ญ ๐€๐ฎ๐ญ๐จ๐ฆ๐š๐ญ๐ข๐จ๐ง ๐š๐ง๐ ๐ƒ๐š๐ญ๐š ๐’๐œ๐ข๐ž๐ง๐œ๐ž. I have ๐’•๐’“๐’‚๐’Š๐’๐’†๐’… ๐’Ž๐’๐’“๐’† ๐’•๐’‰๐’‚๐’ 10,000+ ๐‘ฐ๐‘ป ๐‘ท๐’“๐’๐’‡๐’†๐’”๐’”๐’Š๐’๐’๐’‚๐’๐’” and ๐’„๐’๐’๐’…๐’–๐’„๐’•๐’†๐’… ๐’Ž๐’๐’“๐’† ๐’•๐’‰๐’‚๐’ 500+ ๐’•๐’“๐’‚๐’Š๐’๐’Š๐’๐’ˆ ๐’”๐’†๐’”๐’”๐’Š๐’๐’๐’” in the areas of ๐’๐จ๐Ÿ๐ญ๐ฐ๐š๐ซ๐ž ๐ƒ๐ž๐ฏ๐ž๐ฅ๐จ๐ฉ๐ฆ๐ž๐ง๐ญ, ๐ƒ๐š๐ญ๐š ๐„๐ง๐ ๐ข๐ง๐ž๐ž๐ซ๐ข๐ง๐ , ๐‚๐ฅ๐จ๐ฎ๐, ๐ƒ๐š๐ญ๐š ๐€๐ง๐š๐ฅ๐ฒ๐ฌ๐ข๐ฌ, ๐ƒ๐š๐ญ๐š ๐•๐ข๐ฌ๐ฎ๐š๐ฅ๐ข๐ณ๐š๐ญ๐ข๐จ๐ง๐ฌ, ๐€๐ซ๐ญ๐ข๐Ÿ๐ข๐œ๐ข๐š๐ฅ ๐ˆ๐ง๐ญ๐ž๐ฅ๐ฅ๐ข๐ ๐ž๐ง๐œ๐ž ๐š๐ง๐ ๐Œ๐š๐œ๐ก๐ข๐ง๐ž ๐‹๐ž๐š๐ซ๐ง๐ข๐ง๐ . I am interested in ๐ฐ๐ซ๐ข๐ญ๐ข๐ง๐  ๐›๐ฅ๐จ๐ ๐ฌ, ๐ฌ๐ก๐š๐ซ๐ข๐ง๐  ๐ญ๐ž๐œ๐ก๐ง๐ข๐œ๐š๐ฅ ๐ค๐ง๐จ๐ฐ๐ฅ๐ž๐๐ ๐ž, ๐ฌ๐จ๐ฅ๐ฏ๐ข๐ง๐  ๐ญ๐ž๐œ๐ก๐ง๐ข๐œ๐š๐ฅ ๐ข๐ฌ๐ฌ๐ฎ๐ž๐ฌ, ๐ซ๐ž๐š๐๐ข๐ง๐  ๐š๐ง๐ ๐ฅ๐ž๐š๐ซ๐ง๐ข๐ง๐  new subjects.

Part of seriesData Engineering

Hello everyone, In this blog post i have curated a list of expectation in any job interview for data engineer.

  1. Hands on in Databricks + ADF + Python

  2. Experience in implementing both structured and unstructured data

  3. Streamlining data collection methods to create automated and easy to use routines

  4. Maintaining databases and data systems by addressing errors and monitoring performance

  5. Implementing data migration solutions

  6. Hands on in data warehousing

  7. Detailing out the reference architecture, and implementing it with pattern approved by EA

  8. Working experience in Data processing / ETL / Big data technologies like informatica, Big Data, Kafka, Cloudera, PySpark

  9. Experience in Cloud / Azure architectural components

  10. Experience in building data pipelines and infrastructure

  11. Deep understanding of Data warehousing concepts, reporting and Analytical concepts

  12. Experience with Big Data tech stack, including Hadoop, Spark, Hive and NoSQL data stores.

Thatโ€™s itโ€ฆ Hope you liked this article. Happy Learning:).

I welcome you to connect with me on LinkedIn. For individuals seeking professional guidance and mentorship in the realms of career development and interview preparation, I have commenced mentoring services. Please visit ๐ญ๐จ๐ฉ๐ฆ๐š๐ญ๐ž.๐ข๐จ/๐ง๐š๐ฏ๐ž๐ž๐ง๐ฉ๐ง

#dataengineering#big-data
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Nirmal Saudar2y ago

nice notes concept wise

Data Engineering

Part 12 of 32
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