Data Engineer I, Intelligent Talent Acquisition ID - 1710

Description For Data Engineer I, Intelligent Talent Acquisition

Amazon's Intelligent Talent Acquisition team is seeking a passionate, results-oriented, technical, and inventive Data Engineer to build new data products within the org from the ground up. Come help us to hire the best and enable candidates find their next amazing opportunity!

As a Data Engineer, you should be an expert in the architecture of DW solutions for the Enterprise using multiple platforms. You should excel in the design, creation, management, and business use of extremely large datasets. You should have excellent business and communication skills to be able to work with business analysts and engineers to determine how best to design the data warehouse for reporting and analytics.

Key job responsibilities: You will be responsible for designing and implementing scalable ETL processes in the data warehouse platform to support the rapidly growing and dynamic business demand for data, and use it to deliver the data as service which will have an immediate influence on day-to-day decision making. You should have the ability to develop and tune SQL to provide optimized solutions to the business.

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Basic Qualifications:

  • 1+ years of data engineering experience
  • Experience with data modeling, warehousing and building ETL pipelines
  • Experience with SQL
  • Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
  • Experience with one or more scripting language (e.g., Python, KornShell)
  • Knowledge of cloud services such as AWS or equivalent

Preferred Qualifications:

  • Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
  • Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
  • Master's degree

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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