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Lead Engineer - Data & Analytics
Bangalore, Karnataka, India
Nike does more than outfit the world's best athletes. We are a place to explore potential, obliterate boundaries, and push out the edges of what can be. We're looking for people who can grow, think, dream and create. We thrive in a culture that embraces diversity and rewards imagination. We seek achievers, leaders and visionaries. At Nike, it's about bringing what you have to a challenging and constantly evolving game.
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 help lead our Enterprise Data and Analytics organization, come 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 2020 and beyond.
Nike is embracing Big Data technologies to enable data-driven decisions. We’re looking to expand our Hadoop Engineering team to keep pace. As a lead engineer, you will work with a variety of talented Nike teammates and be a driving force for building solutions for Nike Technology. You will be working on development projects related to consumer behavior, commerce, and web analytics.
DATA ENGINEER RESPONSIBILITIES
- Design and build reusable components, frameworks and libraries at scale to support analytics products
- Design and implement product features in collaboration with business and Technology stakeholders
- Anticipate, identify and solve issues concerning data management to improve data quality
- Clean, prepare and optimize data at scale for ingestion and consumption
- Drive the implementation of new data management projects and re-structure of the current data architecture
- Implement complex automated workflows and routines using workflow scheduling tools
- Build continuous integration, test-driven development and production deployment frameworks
- Drive collaborative reviews of design, code, test plans and dataset implementation performed by other data engineers in support of maintaining data engineering standards
- Analyze and profile data for the purpose of designing scalable solutions
- 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