Nike - Beaverton, OR
posted 2 months ago
Full-time - Mid Level
Beaverton, OR
10,001+ employees
Leather and Allied Product Manufacturing
About the position
As a Senior Data Engineer at NIKE, Inc., you will be responsible for designing, building, and maintaining scalable data pipelines and analytics solutions. This role is crucial for supporting Advanced Analytics and Business Intelligence initiatives within the Consumer Product and Innovation organization. You will collaborate with various teams to ensure robust data products that drive business growth.
Responsibilities
- Design, build, and maintain robust ETL/ELT data pipelines, reusable components, frameworks, and libraries to process data from various sources.
- Collaborate with data engineers, analysts, product managers, and business stakeholders to understand data requirements and deliver data solutions.
- Participate in code reviews, provide feedback, and contribute to continuous improvement of coding practices.
- Identify and tackle issues concerning data management to improve data quality.
- Monitor and troubleshoot data pipelines, ensuring high availability and performance.
- Implement CI/CD pipelines to automate deployment and testing of data engineering workflows.
Requirements
- Bachelor's degree in computer science, engineering, or a related field, or equivalent experience.
- Proven experience (5+ years) as a Data Engineer, focusing on Python, PySpark, and SQL.
- Strong expertise in Apache Spark and distributed computing frameworks, with hands-on experience optimizing Spark jobs for performance and scalability.
- Proficiency in SQL, with the ability to write complex queries and perform data transformations.
- Experience with Databricks Lakehouse Platform, Medallion architecture, and Delta Lake.
- Experience working with AWS, including data-related services such as S3 and RDS.
- Experience with data modeling, ETL/ELT processes, and data warehousing concepts.
- Experience with CI/CD pipelines, version control (Git), and DevOps practices in a data engineering context.
- Excellent problem-solving skills and the ability to design solutions for complex data challenges.
- Ability to communicate effectively with team members and business stakeholders, both verbally and in written form.
Nice-to-haves
- Familiarity with real-time data processing frameworks such as Apache Kafka.
- Knowledge of Generative AI and Machine Learning pipelines and integrating them into production environments.
- Certification in Databricks (e.g., Databricks Certified Data Engineer, Databricks Certified Developer for Apache Spark).
Benefits
- Generous total rewards package
- Casual work environment
- Diverse and inclusive culture
- Professional development opportunities
