Data Engineer - AMZ2818

Job description

DESCRIPTION

MULTIPLE POSITIONS AVAILABLE
Company: Amazon.com Services, Inc., an Amazon.com company
Position Title: Data Engineer
Location: Chicago, IL
Position Responsibilities:
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 engineers. Evaluate and make decisions around the use of new or existing software products and tools. Mentor junior data engineers.

Desired profile

BASIC QUALIFICATIONS

Position Requirements:
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 a 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): Utilizing Redshift databases, DynamoDB, Python, and Lambda; developing and operating large-scale data structures for business intelligence analytics using each of the following: data modeling, SQL, and cloud data technologies.