Become a Part of the NIKE, Inc. Team
NIKE, Inc. does more than outfit the world’s best athletes. It is a place to explore potential, obliterate boundaries and push out the edges of what can be. The company looks for people who can grow, think, dream and create. Its culture thrives by embracing diversity and rewarding imagination. The brand seeks achievers, leaders and visionaries. At NIKE, Inc. it’s about each person bringing skills and passion to a challenging and constantly evolving game.
ABOUT THE ROLE
Now, more than ever, Technology needs to respond quickly to turn market disruptions into opportunities for our world-class brand. To achieve this, we must continue to develop our Enterprise Analytics, Data Science & Machine Learning capabilities and team to ensure we’re maximizing the power of the Nike enterprise in the analytics/machine learning space and managing data as a competitive advantage.
If you’re ready to innovate and be a driving force for building solutions for Enterprise Data and Analytics organization, come to join us now! You will be part of an organization that is revolutionizing Nike technology platforms and architecting a data and analytics landscape that is simplified, modern, flexible and will ultimately enable Nike on its journey to beyond.
WHAT YOU WILL WORK ON
• Design and build reusable data assets for Nike China data lake.
• Anticipate, identify, and solve issues concerning data management to improve data quality.
• Clean, prepare and optimize data at scale for ingestion and consumption.
• Implement complex automated workflows and routines using workflow scheduling tools.
• Drive collaborative reviews of design, code, test plans and dataset implementation performed by other data engineers in support of maintaining data engineering standards.
• Troubleshoot complex data issues and perform root cause analysis to proactively resolve product and operational issues.
• Mentor and develop other data engineers in adopting best practices.
WHO WILL YOU WORK WITH
You will be reporting to the Engineering manager, you will work with Product Manager, other Engineering Team Members and with a variety of talented Nike teammates. You will be part of team that will be a driving force in building Data and Analytic solutions for Nike Technology.
WHAT YOU BRING
• 5~8 years experiencing developing scalable data lake / data warehouse on top of big data platform.
• Good experiences on Python programming language are mandatory.
• Good experiences on Java programming language are preferrable.
• Have deep Knowledge and experiences on Spark SQL / Hive SQL language, good knowledge of Presto or other MPP databases.
• Good knowledge on web application development, AI or other related tech domains will be great plus.
• Have good experiences on Airflow or other data warehouse scheduling tools.
• Have good knowledge on AWS S3, EMR, lambda and AWS components or similar tech stack on other cloud.
• Strong skills building positive relationships across Product and Engineering.
• Able to quickly pick up new programming languages like Java, technologies like EKS, and other well-known frameworks.
• Experience working in Agile and Scrum development process.
• Fluent English skill (including oral and written English)
OUR HIRING GAME PLAN
01 Apply
Our teams are made up of diverse skillsets, knowledge bases, inputs, ideas and backgrounds. We want you to find your fit – review job descriptions, departments and teams to discover the role for you.
02 Meet a Recruiter or Take an Assessment
If selected for a corporate role, a recruiter will reach out to start your interview process and be your main contact throughout the process. For retail roles, you’ll complete an interactive assessment that includes a chat and quizzes and takes about 10-20 minutes to complete. No matter the role, we want to learn about you – the whole you – so don’t shy away from how you approach world-class service and what makes you unique.
03 Interview
Go into this stage confident by doing your research, understanding what we are looking for and being prepared for questions that are set up to learn more about you, and your background.
