Amazon has a culture of data-driven decision-making and demands business intelligence that is timely, accurate, and actionable.
Metrics Guardrails team is seeking a Software Development Engineer who is passionate about building data analytics products designed to uncover customer behavior patterns from the data.
We are looking for a talented engineer who can help building scalable software solutions that processes billions of rows of real world interaction data to deliver business insights on customer behavior.
You will help us answer questions like What is human and what is non-human activity on the retail website? , What data I can trust?
Can we find opportunities for automation in distinguish bad data? , What are the customer profiles that are engaging the most? etc.
Metrics Guardrails is part of Customer Analytics group, responsible for processing big data sets of website traffic in order to identify and understand customer behavior on Amazon websites.
By understanding traffic flows and customer behavior across Amazon websites, we empower data-driven business decisions and forecasts for future of e-
commerce and future device capabilities. Customer Behavior data creates multi-million-dollar business opportunities allowing Amazon strong and sustained growth rates.
As a Software Development Engineer (SDE) you will be working in one of the world's largest and most complex data warehouse environments.
You should be passionate about working with huge data sets, and be someone who enjoy tackle scalability issues and performance optimizations.
As a SDE you will be part of the team, sharing the everyday software development, research process and data curation. You will work under the direct coaching of a dedicated mentor on AWS Stack (EMR, S3, DynamoDB).
You will interact with partner teams to better understand your requirements and receive iterative feedback on your results.
You will implement data analytics using cutting edge analytics patterns and technologies that are inclusive of but not limited to Spark, EMR, Redshift and other in-
house data analysis solutions. The solutions you will design and implement will extract, transform and perform curation on huge volumes of data from various sources and message streams in order to construct complex analyses.
You will write scalable queries and tune performance on queries running over billions of rows of data.
Summarize key insights of complex solutions for technical and non-technical audiences (colleagues from computer science, machine learning and business backgrounds, as well as senior management decision-makers).