Role overview

AWS Data Engineer (Senior)

Requirements and responsibilities

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What you will do?

  • Develop and maintain data pipelines using Amazon EMR or Amazon Glue.
  • Create data models and end-user querying using Amazon Redshift or Snowflake, Amazon Athena, and Presto.
  • Build and maintain the orchestration of data pipelines using Airflow.
  • Collaborate with other teams to understand their data needs and help design solutions.
  • Troubleshoot and optimize data pipelines and data models.
  • Write and maintain PySpark and SQL scripts to extract, transform, and load data.
  • Document and communicate technical solutions to both technical and non-technical audiences.
  • Stay up-to-date with new AWS data technologies and evaluate their impact on our existing systems.

What are we looking for?

  • Bachelor's degree in Computer Science, Engineering, or a related field.
  • 3+ years of experience working with PySpark and SQL.
  • 2+ years of experience building and maintaining data pipelines using Amazon EMR or Amazon Glue.
  • 2+ years of experience with data modeling and end-user querying using Amazon Redshift or Snowflake, Amazon Athena, and Presto.
  • 1+ years of experience building and maintaining the orchestration of data pipelines using Airflow.
  • Strong problem-solving and troubleshooting skills.
  • Excellent communication and collaboration skills.
  • Ability to work independently and within a team environment.

You are preferred if you have

  • AWS Data Analytics Specialty Certification
  • Experience with Agile development methodology
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Browse stack
FocusData EngineeringRole area
Seniority signalSeniorCandidate level
StackAWS, Snowflake, SQLPrimary skills
Location1 accepted countryEligibility

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