The Supply Chain Optimization Technology (SCOT) owns Amazon's global inventory planning and fulfillment systems. SCOT decides what, when, who, where, and how much inventory to buy in order to meet customer needs as well as Amazon's business goals. SCOT optimizes transportation and fulfillment plans to help our Customers get what they need, as fast as possible. We do this for millions of items, for hundreds of product lines worth billions of dollars of inventory world-wide. See this short video for more info: http://bit.ly/amazon-scot.
The Fulfillment Availability Team is part of SCOT and we own several core systems that are at the foundation of Amazon's fulfillment pipeline and supply chain. We track inventory signals globally, in real time, and provide transactionally precise data on top of robust and asynchronous systems. We manage the complex graphs, constraints, and rules that define the Amazon fulfillment network and how things move through. We enable fulfillment of anything everywhere.
If you are interested in engineering the metrics model that drives continuous improvement for Amazon's Fulfillment Network, then the Fulfillment Availability Analytics Team (FAA) is the right place for you!
FAA Team seeks an enthusiastic, customer obsessed Data Engineer to create the data infrastructure and pipelines necessary to drive initiatives behind operational challenges that will set the pace for the next generation of Amazon Logistics.
You will apply Large-scale computing, Distributed systems, Data mining, Scalability, Machine learning and Statistical Algorithms techniques - just to name a few.
Our Data Engineer needs to be able to gather and understand data requirements, present it to software engineers, and work in the team to achieve high quality data ingestion goals. You need a passion for complex problems, data quality and enjoy the challenge of operating complex systems. Do you think you are up to the challenge? Would you like to learn more and stretch your skills and career?
In this role, you will be a technical expert with significant scope and impact. You will work closely with a group of Software Development Engineers, Business Intelligence Engineers and Data Scientists to create the data infrastructure and pipelines necessary to drive our team's initiatives.
Successful candidates should come from a strong data engineering background. You need to have experience with structured data, and being able to analyze/transform the data using various tools. Although SQL is a strong requirement, being flexible enough to work in a scripting environment is a must. Often, the pace of innovation and change implies a need to move to new data sources, and our Data Engineers will get to participate in deep diving business data in order to understand/measure sources of disparity. Your analytical skills and knowledge of schema metadata will be essential.
Key job responsibilities
Create and maintain data transformation logic, create scalable data solutions, use data clusters of 50+ nodes.BASIC QUALIFICATIONS
- Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical discipline. Master's degree is a definite plus.
- 4+ years of industry experience in Software Development, Data Engineering, Business Intelligence or related field with a solid track record of manipulating, processing, and extracting values from large datasets.
- Hands-on experience and highly advanced knowledge of SQL, Data Modeling, ETL Development, and Data Warehousing.
- Experience with working with multi-node data clusters
- Solid experience using big data technologies (Redshift, Hadoop, Hive, Hbase, Spark, EMR, etc.).
- Knowledge and experience with Data Management and Data Storage best practices.
- Strong customer focus, ownership, and ability to deliver results.
- Excellent communication and collaboration skills
- Effective analytical, troubleshooting, and problem-solving skills.
- Masters in computer science, mathematics, statistics, economics, or other quantitative fields.
- Experience working with AWS big data technologies (Redshift, S3, EMR, Glue).
- Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy.
- Experience providing technical leadership and educating other engineers for best practices on data engineering.
- Background in Big Data, non-relational databases, Machine Learning and Data Mining is a plus.
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, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.