Data Engineer, Amazon

• The ideal candidate thrives in a fast-paced environment, relishes working with ambiguity, big data, and enjoys the challenges of highly complex business context
• This role requires an individual with a strong data modeling background, deep knowledge of cloud infrastructure, optimizing data for business intelligence solutions, and the ability to quickly learn, adapt and work with a variety of technologies
• You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions, and build data sets that answer those questions
• You should be able to architect highly efficient data and reporting structures, making a tradeoff between scalability, performance and user functionality needs, using expert knowledge in software development technologies
• This role requires an individual with excellent analytical abilities, deep knowledge of business intelligence solutions, and the ability to quickly learn, adapt and work with a variety of technologies
• Experience as a Data Engineer or in a similar role
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
• Experience with one or more scripting language (e.g., Python, KornShell)
• Experience with SQL

Desirable

• The Accounting BI team supports the global Accounting organization with process automation/improvements, developing automated reporting solutions/tools, and improving the ability of the accounting organization to process, analyze, access and consume accurate and timely financial data
• The team supports the global accounting organization and partners closely with all technical roles across the org and various businesses and industries Amazon operates in
• Working with stakeholders and other engineering teams to identify and scope the right data architecture and technology to be used to facilitate analysis of most common Amazon customer behavioral questions
• Partnering with partner engineering teams to enhance data infrastructure, data availability, and broad access to customer insights made available through BI tools across the organization
• Design, build and implement the right ETL processes using AWS and similar technologies
• Implement anomaly detection systems to have a proactive approach to any potential data quality issues, using industry standard frameworks
• Enable large scale analytics using EMR and other big data technologies
• Establishing and implementing technology best practices that should be followed across the organization
• Work on proof of concepts for adoption of new technology and tools