Lead Data Engineer

Lead Data Engineer - NIKE USA Inc.- Beaverton, OR. 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. Identify and solve issues concerning data management to improve data quality. Clean, prepare and optimize data for ingestion and consumption. Collaborate on the implementation of new data management projects and re-structure of the current data architecture. Implement automated workflows and routines using workflow scheduling tools. Build continuous integration, test-driven development and production deployment frameworks. Review design, code, test plans and dataset implementation performed by other data engineers in support of maintaining data engineering standards. Analyze and profile data for designing scalable solutions, troubleshoot data issues and perform root cause analysis to proactively resolve product and operational issues. Develop architecture and design patterns to process and store high volume data sets. Participate in an Agile or Scrum methodology to deliver high quality software releases through sprints. Propose architectural solutions and build ETL design documents, such as low-level design and high-level design documents, for the business use cases. Participate in resource intake that provide solutions and resolutions to stakeholders to solve project issues, in the setup of teams for smooth execution, and presenting project demos to clients and stakeholders. Telecommuting is available from anywhere in the U.S., except from SD, VT, and WV. 

Must have Bachelor’s degree in Computer Science, Information Technology, or Computer Information Systems and 5 years of progressive post-baccalaureate experience in the job offered or a computer-related occupation.

Experience must include: 

• Databricks 

• PySpark 

• Python 

• Snowflake 

• AWS cloud 

• AWS solutions architect 

• Airflow 

• Javascript 

• AWS Sagemaker 

• Jenkins 

• Dynamo DB 

• Power BI 

• SSAS Cube