Big Data Engineer Skills

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Data engineers need to know a combination of programming languages, database skills, and data processing tools in order to be successful in their careers.

Also need to have understanding of below technology

  1. Big Data Processing Frameworks: Apache Hadoop, Apache Spark, Apache Storm, and Apache Flink are some of the popular big data processing frameworks used in the industry.
  2. Distributed Storage Systems: Experience with distributed storage systems such as HDFS, Apache Cassandra, and Apache Kafka is essential for a data engineer.
  3. Data Warehousing: Knowledge of data warehousing technologies such as Apache Hive, Apache Impala, and Apache Pig is also important.
  4. Data Integration: Experience with data integration technologies such as Apache NiFi, Apache Nifi Registry, Apache Airflow, and Apache Beam is important.
  5. Cloud Computing: Familiarity with cloud computing platforms such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) is important, as many data engineering jobs at FAANG companies involve working with data stored in the cloud.
  6. SQL and NoSQL databases: Knowledge of SQL databases such as MySQL, PostgreSQL, and Oracle and NoSQL databases such as MongoDB, Cassandra, and Hbase is also important.
  7. Programming languages: Familiarity with programming languages such as Python, Java, and Scala is essential for a data engineer.
  8. Data Governance and Security: Understanding of data governance and security best practices, including data encryption, access controls, and compliance requirements is necessary.

It's important to note that, these technologies keep evolving, so it's important to keep yourself updated with new technologies, methodologies, and industry best practices.

In my blog post and in my YouTube channel I am going to discuss all of the above topics.

Link for YouTube Channel

https://www.youtube.com/c/fylfotbeta



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