WHO YOU’LL WORK WITH

You will report to the Data Engineering Supervisor who is based at our Converse India Tech Center. You will work hand-in-hand with the data engineering squad, product management team, and production support team, along with a variety of dedicated Converse and Nike partners focused on technology solution delivery, architecture, and platforms. 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 continue growing 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 2 years relevant work experience
•Bachelor’s degree or equivalent combination of education, experience or training

WHAT YOU’LL WORK ON

As a Data Engineer on the Enterprise Data & Analytics team, you will drive work to completion with hands-on development responsibilities, and partner with the Lead Engineers to deliver quality components of a data product. You will build 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.

•Design and build reusable components of a larger process or framework to support analytics products with guidance from experienced peers
•Design and implement simple product features in collaboration with business and Technology stakeholders
•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
•Understand and use current continuous integration, test-driven development and production deployment frameworks
•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.