Senior Data Engineer

Senior Data Engineer
Fully Remote, United States
Published
April 28, 2021
Location
Fully Remote, United States
Job Type
Category
IT

Description

SHR Talent is currently representing a company in Chattanooga, TN in its search for a full-time Senior Data Engineer. This is a 100% remote opportunity. The successful candidate in this role will be an experienced software engineer with significant contributions in data.

 

General Responsibilities:

  • Identify, prioritize, and inform important business questions with data. These outputs will directly influence our product roadmap.
  • Work with several analysts throughout the company to dive deep into business metrics and help drive data-driven decisions.
  • Develop new data pipelines. Improve and maintain existing data pipelines and data warehouses. Ship stable, high quality solutions at a fast pace.
  • Empower data scientists to solve real world problems by improving their workflow. Help design innovative solutions for cutting edge machine learned solutions.
  • Be a champion for data. Envision a world different than the status quo and articulate a clear path for everyone in the company to get there.

Qualifications:

  • BS/MS in Computer Science, Electronics, Electrical, Statistics, Applied Mathematics, or related field
  • 5+ years of industry experience in a software engineering role using python or Scala
  • Familiarity with Machine learning concepts and frameworks: Scikit-learn, numpy, scipy.
  • Proficiency in querying, manipulating and analyzing large data sets using SQL
  • Familiarity with Apache Spark
  • Experience with managed data engineering services from public cloud providers is a plus (e.g., services from AWS or Google Cloud)
  • Experience with Tableau is a plus
  • Deep experience in one or more of: ETL, data warehousing, data visualization.
  • Previous experience scraping 3rd-party API’s and cleaning external datasets.
  • Ability to clearly communicate and articulate results to both technical and non-technical audiences.
  • Bias for action and an appreciation for the knowledge-impact sweet spot
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