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Proficiency in programminglanguages Even though in most cases data architects don’t have to code themselves, proficiency in several popular programminglanguages is a must. Let’s start from the hard skills and discuss what kind of technical expertise is a must for a data architect.
NoSQL – This alternative kind of data storage and processing is gaining popularity. The term “NoSQL” refers to technology that is not dependent on SQL, to put it simply. Python – The most popular programminglanguage nowadays is Python, which is ranked third among programmers’ favorites.
This job requires a handful of skills, starting from a strong foundation of SQL and programminglanguages like Python , Java , etc. Generalists They are typically responsible for every step of the data processing, starting from managing and making analysis and are usually part of small data-focused teams or small companies.
Python Python is one of the most looked upon and popular programminglanguages, using which data engineers can create integrations, data pipelines, integrations, automation, and data cleansing and analysis. NoSQL If you think that Hadoop doesn't matter as you have moved to the cloud, you must think again.
For small companies, the data engineer holds a generalist position where he basically does all it. Learn Key Technologies ProgrammingLanguages: Language skills, either in Python, Java, or Scala. Databases: Knowledgeable about SQL and NoSQL databases. Why Choose Data Engineering as a Career?
Data engineers play three important roles: Generalist: With a key focus, data engineers often serve in small teams to complete end-to-end data collection, intake, and processing. The generalist position would suit a data scientist looking for a transition into a data engineer.
ProgrammingLanguages : Good command on programminglanguages like Python, Java, or Scala is important as it enables you to handle data and derive insights from it. Develop working knowledge of NoSQL & Big Data using MongoDB, Cassandra, Cloudant, Hadoop, Apache Spark, Spark SQL, Spark ML, and Spark Streaming 18.
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