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Senior Data Engineer

Cincinnati, Ohio
US$130000 - US$140000 per annum
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Senior Data Engineer
Consumer Products
Cincinnati, OH
$130,000 - $140,000

THE COMPANY:

They are a consumer brands corporation representing hundreds of brands you see every day. They have revolutionized how we buy products today. Its mission is to create the best buying experience for its customers and while keeping high standers in its products.

THE ROLE - Senior Data Engineer

As a Senior Data Engineer, you build data pipelines in multiple cloud environments. You are comfortable with embracing a lack of structure and like to shape an outcome. You will be working closely with data science teams to build/maintain data pipelines, increase data quality, increase data speed, etc. Your responsibilities will include:

  • Building the end to end data pipelines using Python for Data Science teams
  • Be comfortable working in an experimental department
  • Working with one of these cloud services GCP, Azure, or AWS. You will have the chance to learn one or more that you haven't worked with before
  • Using Airflow for job scheduling
  • If you like a challenge and want to learn new skills, this is the role for you

YOU WILL NEED:

  • Commercial experience in designing data pipelines from scratch
  • Strong programming experience with Python
  • Commercial experience with one or more cloud services AWS, Azure, or GCP
  • Experience with Java and Scala is a plus
  • Bachelors or master's in computer science, data science, data engineering, or related

THE BENEFITS:

  • $130,000 - $140,000 base salary
  • Annual bonus
  • Pay for relocation
  • Health benefits
  • 401K
  • PTO and sick time off

HOW TO APPLY

Please register your interest by sending your resume to Jacob Ragland via the Apply link on this page.

KEYWORDS

Python, AWS, ELT, ETL, AI, Engineer, SQL, pipeline, data, software, Developer, Airflow, Software, Data Engineering, git, NoSQL, CGP, Azure, AKS, Kubernetes

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98504/jr JAR#9
Cincinnati, Ohio
US$130000 - US$140000 per annum
  1. Permanent
  2. Big Data

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