MULTIPLE POSITIONS AVAILABLE
Entity: Amazon.com Services LLC, an Amazon.com Company
Job Title: Data Engineer II
Location: San Diego, CA
Design, develop, implement, test, document, and operate large-scale, high-volume, high-performance data structures for business intelligence analytics. Implement data structures using best practices in data modeling, ETL/ELT processes, SQL, and cloud technologies. Provide on-line reporting and analysis using business intelligence tools and a logical abstraction layer against large, multi-dimensional datasets and multiple sources. Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions that work well within the overall data architecture. Analyze source data systems and drive best practices in source teams. Participate in the full development life cycle, end-to-end, from design, implementation and testing, to documentation, delivery, support, and maintenance. Produce comprehensive, usable dataset documentation and metadata. Evaluate and make decisions around dataset implementations designed and proposed by peer data engineers. Evaluate and make decisions around the use of new or existing software products and tools. Mentor junior data engineers.
Amazon.com is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.#0000
Master’s degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field and one year of experience in the job offered, or as an Operations Research Analyst, Database Developer, or a related occupation. Employer will accept a Bachelor’s degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field and five years of experience in the job offered or a related occupation as equivalent to the Master’s degree and one year of experience. Must have one year of experience in the following skill(s): experience working with a modern programming language such as Python, Ruby, or Java; developing and operating large-scale data structures for business intelligence analytics using each of the following: ETL/ELT processes; cloud technologies; data modeling; SQL; and HIVE.
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