Data Engineer, Data : Science Engineering, AWS Marketing, Data : Science Engineering, AWS Marketing, TAA-Data: Science & Engineering

Seattle, WA (Unknown)

$101K/yr – $160K/yrMid Level1+ years expFull time

Posted 2 weeks ago

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Job Summary

Own and evolve a scalable data engineering platform in AWS, integrating diverse data sources into Jarvis and delivering robust datasets for reporting and growth.

  • Own design and operation of data integration pipelines
  • Collaborate with business owners to translate questions into data sets
  • Drive improvements across ad-hoc data access and reporting workloads

Job Description

Responsibilities

  • As a Data Engineer at AWS, you will be working in a large, extremely complex and dynamic data warehousing environment.
  • We are looking for someone with the uncanny ability to integrate multiple heterogeneous data sources with AWS Marketing Data Warehouse - Jarvis and build efficient, flexible, and scalable data warehouse and reporting solutions.
  • You should be enthusiastic about learning new technologies and be able to implement solutions using these technologies to enable upgrades of the existing platform.
  • You should have excellent business and communication skills and be able to work with business owners to develop and define key business questions, then build the data sets that answer those questions.
  • You should be expert at designing, implementing, and operating stable, scalable, low cost solutions to flow data from production systems into the data warehouse and into end-user facing reporting applications.
  • Above all you should be passionate about working with huge data sets and someone who loves to bring datasets together to answer business questions and drive growth.
  • A day in the life
  • Design, implement, and support a platform providing ad-hoc access to large datasets
  • Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL
  • Build robust and scalable data integration (ETL) pipelines using SQL, Python and AWS services such as Data Pipelines, Glue

Requirements

  • 1+ years of data engineering experience
  • Experience with data modeling, warehousing and building ETL pipelines
  • 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)

Preferred

  • 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

Benefits

  • Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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Marketing Team

Median Career Experience
7 years
Median Tenure
4.5 years
Marketing Roles Posted (Last 30 Days)
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