8 - 13 years

27 - 37 Lacs

Posted:2 hours ago| Platform: Naukri logo

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Job Type

Full Time

Job Description

  1. Denodo
  2. Azure Databricks
  3. Azure Data Factory
  4. Snowflake
  5. PySpark

Good-to-Have

  1. SQL
  2. Azure Services like Key Vault, Storage Account, IAM, etc.
  3. DevOps
  4. Understanding/Experience of Support Processes
  5. Python

SNResponsibility of / Expectations from the Role 1

  • Debug mode can be helpful when trying out pipeline code and acts as a tool to test and troubleshoot our code.
  • Manual Execution is what we do by clicking on the Trigger now option in a pipeline. This is useful if you want to run your pipelines on an ad-hoc basis.
  • We can schedule our pipelines at predefined times and intervals via a Trigger. As we will see later in this article, there are three types of triggers available in Data Factory.

What types of SQL commands (or SQL subsets) do you know?

  • Data Definition Language (DDL)

    to define and modify the structure of a database.
  • Data Manipulation Language (DML)

    to access, manipulate, and modify data in a database.
  • Data Control Language (DCL)

    to control user access to the data in the database and give or revoke privileges to a specific user or a group of users.
  • Transaction Control Language (TCL)

    to control transactions in a database.
  • Data Query Language (DQL)

    to perform queries on the data in a database to retrieve the necessary information from it.

Is Snowflake an ETL tool?

  • RDDs are low-level APIs that lack a schema and offer control over the data. They are immutable collections of objects
  • DataFrames are high-level APIs built on top of RDDs optimized for performance but are not safe-type. They organize structured and semi-structured data into named columns.
  • Datasets combine the benefits of RDDs and DataFrames. They are high-level APIs that provide safe-type abstraction. They support Python and Scala and provide compile-time type checking while being faster than DataFrames.

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