Big Data Engineer, Jobs #95 Issue

Hello, Hola, & Namastey! This is your Host & Dost (Friend),  Rahul Sharma, Welcoming you to the most active community of Job Seekers: The Remote Profile family.

As a Remote Profile family, we help everyone land their dream remote job offer.

Today, it is going to be different because we have selected a unique field of data, i.e., Big Data.

We will learn something about Big Data and will apply to one job that is available in the market. As this market is still growing, there are not so many remote jobs available for the same. But we will provide whatever upcoming opportunities will come.

Without any further delay, I welcome you all to our #95 Issue…( So, Close to hitting a century, I am excited as hell, and I am guessing the same for you too… coz that will be awesome.)

Welcome Everyone

Big Data Engineer: Making data work for you!

Big data refers to large, complicated datasets that are challenging to process with typical data management techniques. These datasets are frequently distinguished by the "three Vs":

  • Volume: is related to the size of the data

  • Velocity: refers to the speed of generation of data

  • Variety: comprises a variety of data

Below are some examples of large data:

Social media data: Every day, billions of individuals create data on sites such as Facebook, Twitter, and Instagram. This data may contain text, photographs, videos, and even location information.

Sensor data: Sensors are becoming more prevalent in our homes, businesses, and even our bodies. These sensors collect information on anything from temperature and humidity to heart rate and blood pressure.

Transaction data: When we make a purchase, swipe a credit card, or use a loyalty card, we create transaction data. This information can be used to monitor purchasing patterns, analyze trends, and tailor advertisements.

There are some Technical Skills which you must have to grow in the Big Data field:

  • Programming Languages: Strong knowledge of at least one programming language is required, with Python being the most common choice due to its versatility and large data science libraries. Depending on your area of specialization, other languages such as Java, C++, and Scala can be useful.

  • Databases: Learn about relational (SQL) and non-relational (NoSQL) databases for data storage and retrieval. Familiarity with cloud-based database solutions such as Amazon Redshift, Azure SQL Database, and Google Cloud SQL is advantageous.

  • Big Data tools and frameworks: Master Hadoop's ecosystem, which includes HDFS, MapReduce, YARN, Hive, and Pig. Gain knowledge of Apache Spark for distributed data processing and streaming analytics. Learn about other useful tools such as Kafka for data streaming, Airflow for workflow management, and ELK Stack for log analysis.

  • Cloud Computing: Experience with major cloud platforms such as AWS, Azure, and GCP is required. Understanding how to create and implement cloud-based data pipelines and infrastructure is a valuable ability.

  • DevOps skills: Knowledge of Git version control, CI/CD pipeline, and automation tools like Jenkins is becoming increasingly vital for big data engineers who must communicate successfully and release data solutions rapidly.

Now, It’s time for the Jobs Section:

Before I sign off, I want your help, everyone, Please Let me know what you would like to see in the future. You can reach out to me via  Rahul Sharma, I love to assist you and help you via this platform.

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 Motivational Quote of the Day 

"Fear is not evil. It tells you what your weakness is. And once you know your weakness, you can become stronger as well as kinder." — "Fairy Tail", 2009.

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