This position is no longer active. The listing is kept for reference.
WHO YOU’LL WORK WITH You will partner with globally distributed teams of engineering, product and program teams to ensure that the ecosystem of services remains loosely coupled, independently scalable, and meets the needs of the business.
You will participate in designs and implementation on a team building high-throughput, low-latency, fault-tolerant Paid Media solutions to drive Nike’s Digital transformation and growth strategies. The candidate needs to have • strong communication skills, help solve complex problems, and be a collaborative teammate. A minimum of 4 years software development • experience in data engineering with • experience in Python or Java, Databricks, Hive, Spark, EMR and SQL Demonstrated strength in data modelling, ETL development, and data streaming Knowledge of data management fundamentals and data storage principles Familiarity with the challenge of moving large files across a geographically disperse network.
of deploying and supporting the software in production Experience with highly collaborative, multi-discipline development team environments Experience with developing automated tests (E2E) with testing frameworks Solid understanding of Scrum and Agile principles Dedication to and hands-on • experience in performing technical code reviews Excellent verbal and written communication and collaboration skills to effectively connect with both business and technical teams Bachelor’s degree in Computer Science or Engineering, Information Systems, or a combination of relevant education, experience, and training WHAT YOU’LL WORK ON You will build and deliver the technical runway for existing and new technological capabilities to support multiple mission critical systems within the Paid Media space.
You will rely on your understanding of scalable, highly available, and consistent distributed systems to design world class solutions.
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Salary: $80,000 - $125,000
🤖 This salary estimate is calculated by AI based on the job title, location, company, and market data. Use this as a guide for salary expectations or negotiations. The actual salary may vary based on your experience, qualifications, and company policies.
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