Data Engineer I, Global Converse, ITC
Posted 2025-05-18
Remote, USA
Full-time
Immediate Start
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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