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# Data Engineer II - AMZ10595704

- **Company:** Amazon.com, Inc.
- **Location:** Denver, CO, United States
- **Salary:** $145,787.0 - $178,800.0
- **Contract:** Permanent contract
- **Skills:** Abstraction Layers, Information Systems, Databases, Data Architecture, Extract Transform Load (ETL), Data Structures, Online Analytical Processing, Oracle Business Intelligence Enterprise Edition, Oracle (Applications), Software Engineering, SQL Databases, Information Technology
- **Published:** October 15, 2026
- **Apply:** https://www.careerjet.com/job/usdeea897431c8a486a1eed1e96176df54/eaa

## About the Role

Master's degree or foreign equivalent degree 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 degree in Computer Science, Engineering, Information Systems, Mathematics, or a related field and five years of progressive post-baccalaureate 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): (1) developing and operating large-scale data structures for business intelligence analytics using each of the following: (i.) ETL/ELT processes; (ii.) OLAP technologies; (iii.) data modeling; (iv.) SQL; and (v.) Oracle.#0000

## Description

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, Oracle, and OLAP technologies. Provide on-line reporting and analysis using OBIEE 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