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Data Engineer I, Global Converse, ITC

Worldwide Salaried Open

WHO YOU’LL WORK WITH You will report to the Data Engineering Supervisor who is based at our India Tech Center. You will work hand-in-hand with the data engineering squad and product management team along with a variety of dedicated Nike partners. You will join a highly motivated, global team that will be a driving force in building Data and Analytic solutions for the Converse Enterprise. WHO WE ARE LOOKING FOR We are looking for someone who is eager to grow their career in the ever-evolving world of data & analytics. The right candidate can quickly pick up new programming languages, technology concepts, and frameworks. They have strong problem-solving skills and an understanding of data structures and algorithms. They thrive in a hard-working team environment, and have an ability to both influence and communicate effectively with team members and business stakeholders alike.

  • Experience with relational SQL and scripting languages such as Python
  • Experience with source control tools such as GitHub
  • Knowledge of scalable, cloud data solutions, preferably AWS
  • A passion for data solutions and winning as a team
  • Minimum 1 year relevant work experience
  • Bachelor’s degree or equivalent combination of education, experience or training

WHAT YOU’LL WORK ON You will build small, well-defined, reusable components of a larger data pipeline to support data analytics products with guidance from experienced peers, all while working within an agile framework that focuses on delivering incremental value.

  • Solve straightforward data management issues to improve overall data quality.
  • Clean, prepare and optimize data for ingestion and consumption
  • Support the implementation of new data management projects and re-structure of the current data architecture
  • Implement simple automated workflows using workflow scheduling tools, such as Matillion or Brickflow
  • Participate in design, code and test plan reviews to increase knowledge and application of best practices
  • Analyse and profile data for the purpose of designing components of a scalable solution
  • Troubleshoot straightforward data issues and perform root cause analysis to resolve product issues

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