Roadmap to Becoming a Data Engineer by Brij kishore Pandey
by
Jayavel Chakravarthy Srinivasan
- 3:54 PM
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𝟭. 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 :
Data engineers require proficiency in at least one programming language like Python, Java, or Scala. These languages are crucial for developing and maintaining data pipelines, building data models, and performing various data engineering tasks.
𝟮. 𝗠𝗮𝘀𝘁𝗲𝗿𝗶𝗻𝗴 𝗦𝗤𝗟:
Structured Query Language (SQL) is the standard for querying and manipulating data in relational databases. Data engineers rely heavily on SQL to work with data pipelines, data warehouses, and other data storage systems.
𝟯. 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 𝗗𝗮𝘁𝗮 𝗪𝗮𝗿𝗲𝗵𝗼𝘂𝘀𝗶𝗻𝗴 𝗮𝗻𝗱 𝗕𝗶𝗴 𝗗𝗮𝘁𝗮 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀:
A solid understanding of data warehousing and big data technologies is essential for building and maintaining data pipelines and data warehouses.
𝟰. 𝗖𝗹𝗼𝘂𝗱 𝗖𝗼𝗺𝗽𝘂𝘁𝗶𝗻𝗴 𝗘𝘅𝗽𝗲𝗿𝘁𝗶𝘀𝗲:
Cloud platforms like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure are widely used by data engineers to manage and build data pipelines and warehouses. Familiarity with these platforms is crucial.
𝟱. 𝗛𝗮𝗻𝗱𝘀-𝗼𝗻 𝗘𝘅𝗽𝗲𝗿𝗶𝗲𝗻𝗰𝗲 𝘄𝗶𝘁𝗵 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗧𝗼𝗼𝗹𝘀:
Several tools facilitate building and managing data pipelines, data warehouses, and performing various data engineering tasks. These include:
• Apache Airflow: https://lnkd.in/e-7JUPgQ
• AWS Glue: https://lnkd.in/eVEWRjRi
• Google Cloud Dataflow: https://lnkd.in/e9--s3FS
• Azure Data Factory: https://lnkd.in/ehGryJqw
𝟲. 𝗕𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗮 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗣𝗼𝗿𝘁𝗳𝗼𝗹𝗶𝗼:
Once you have a strong foundation in the essential skills and tools, focus on creating a portfolio of projects showcasing your skills to potential employers. Many project ideas and tutorials are available online. Alternatively, consider contributing to open-source data engineering projects.
𝟳. 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝗶𝗻𝗴 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗗𝗮𝘁𝗮 𝗘𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆:
Networking with other data engineers is a valuable way to learn about new technologies and trends, discover job opportunities, and build your professional network. You can connect with them online through social media, forums, and meetups, or attend industry-specific conferences and workshops.
𝗔𝗱𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗖𝗼𝗻𝘀𝗶𝗱𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝘀:
Remember, this roadmap is a general guideline, and specific requirements might vary depending on your desired career path. It's also crucial to continuously update your knowledge and skills to stay relevant in the data landscape.
Tags:
#DataEngineering, #DataScience, #LearningRoadmap, #Data Science
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