Data Engineer II, Chronicle
Seattle, Washington, USA
Amazon.com
Free shipping on millions of items. Get the best of Shopping and Entertainment with Prime. Enjoy low prices and great deals on the largest selection of everyday essentials and other products, including fashion, home, beauty, electronics, Alexa...Ever wondered how Amazon offers the Earth's biggest selection and still manages to offer lower prices every day to our customers? Our consumer business teams work with a massive array of selling partners and business financial performance metrics to expand selection and drive costs lower. Given the rapid growth of our business, this requires our category leaders, financial analysts, account managers, site merchandisers and vendor managers to quickly analyze vendors, merchants, categories and brands, diving deep into data showing business efficiency down to the unit sale level. The technology that enables this has huge visibility and impact and is critical to Amazon's continued profitability and growth.
Innovation
We're working on the future. If you are seeking an environment where you can drive innovation. If you want to apply state-of-the-art software technologies to solve real world problems. If you want the satisfaction of providing visible benefit to end-users in an iterative fast paced environment, this is your opportunity. The responsibilities of this role will be key in paving the future of Amazon Consumer and transforming how we do business.
Key job responsibilities
Our team is within the Selling Partner Services organization and develops sophisticated tools for the Amazon Consumer businesses, supporting deep dive analysis, vendor negotiations and business planning towards enhancement at the bottom line. We also provide financial and operational reports to Amazon retail vendors worldwide.
You will be part of a team of creative, top-notch software and data engineers to work hard, have fun, and make history. Engineers at Amazon are more than just order takers; they see a problem and leverage innovative technology to address it. You will be working with very large data sets, well beyond the scalability limits of conventional relational databases. We're looking for people who innovate, love solving hard problems, and never take "no" for an answer.
Basic Qualifications
- Bachelor’s degree or higher in an analytical area such as Computer Science, Physics, Mathematics, Statistics, Engineering or similar.
- 5+ years relevant professional experience in Data Engineering and Business Intelligence
- 3+ years in with Advanced SQL (analytical functions), ETL, DataWarehousing.
- Strong knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures, data modeling and performance tuning.
- Advanced data analysis skills
- Experience with AWS services including S3, Redshift, EMR
- Knowledge of distributed systems as it pertains to data storage and computing
- Ability to effectively communicate with both business and technical teams.
Preferred Qualifications
- Experience on working with Big Data
- Knowledge of Map Reduce, Spark and Presto
- Experience providing technical leadership and mentoring other engineers for best practices on data engineering
- Knowledge of software engineering best practices across the development life-cycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile Architecture AWS Big Data Business Intelligence Computer Science Data analysis Data warehouse Data Warehousing Distributed Systems ELT Engineering ETL Map Reduce Mathematics Physics RDBMS Redshift Spark SQL Statistics Testing
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