Job Description

Summary:
We are seeking a highly skilled Data Engineer to design, build, and maintain large-scale data pipelines in a fully remote role. The ideal candidate has expertise in AWS, Spark, and Python, with experience in optimizing ETL pipelines and implementing scalable data solutions. This role involves collaboration with cross-functional teams to ensure data integrity, security, and performance.

Position Info:

• Title: Data Engineer
• Client: Nike
• Duration: 18-month minimum contract w/ extensions
• Location: Beaverton, OR
• Work Mode: Remote

Responsibilities:

• Design and maintain large-scale data pipelines using AWS EMR, Spark, and Python.
• Develop and optimize Spark applications and ETL pipelines for performance and scalability.
• Collaborate with product managers and analysts to design data models and warehousing solutions.
• Ensure data quality, integrity, and security across all data systems.
• Implement CI/CD pipelines for automated testing and deployment.
• Work with DevOps teams to ensure seamless deployment of data applications.
• Stay up to date with industry trends in big data and cloud computing.

Skills/Qualifications:

• 5+ years of experience in data engineering or big data.
• Expertise in Spark (Spark Core, Spark SQL, Spark Streaming).
• Experience with AWS EMR, including cluster management and job optimization.
• Strong Python skills, including data structures and algorithms.
• Hands-on experience with Databricks (Databricks Lakehouse preferred).
• Knowledge of data modeling, data warehousing, and data governance.
• Experience with CI/CD tools (Jenkins, GitLab, CircleCI preferred).
• Strong problem-solving skills and ability to debug complex data issues.
• Excellent communication and collaboration skills.

Nice to Have:

• Experience with Databricks Lakehouse.
• Knowledge of data engineering best practices and design patterns.
• Experience with Agile development methodologies (Scrum, Kanban)

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