Amazon is looking for a Analytics Engineer to join the Selling Partner Paid Services -Data & Analytics team. This team specifically focuses on growing the Selling Partner business profitability by partnering with them to provide actionable recommendations. Our team is building a recommendation platform to help Selling Partners grow their businesses on Amazon. Our culture is to make metrics-driven decisions. We generate tons of metrics and analyze them to continuously raise the bar on our recommendations. We aggressively embrace AWS technologies like DynamoDB, S3, Kinesis, SQS/SNS, Firehose, Lambda, Elastic Search, EC2, Redshift continuously to scale our ecosystem.
We are looking for a team-player to play a significant part in defining our team efforts. The successful candidate will be a self-starter, comfortable with ambiguity and be able to create and maintain efficient & automated processes. They will have to set the right vision, strategy and road map and work alongside with stakeholders in the organization to make it happen.
We are seeking an outstanding Analytics Engineer to join our team. You will have fun designing, prototyping and building insights, data pipelines, and awesome user experiences. We are looking for a talented, hands-on developer, who takes pride in building simple solutions for complex problems, and continuously raises the bar in coding excellence, design and development process. If you are a proactive problem solver that easily balances trade-offs between competing interests; thrive in an environment where you can give direction in order to create the optimal solution; your solutions are technically precise and easily understood, we want to hear from you!
* Lead architecture design and implementation of next generation BI solution.
* Build robust and scalable data integration (ETL) pipelines using SQL, EMR, Python and Spark.
* Mentor and develop other DE's and BIE's.
* Build and deliver high quality data architecture to support business analyst, data scientists, and customer reporting needs.
* Interface with other technology teams to extract, transform, and load data from a wide variety of data sources.
* Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
* Drive deep understanding of Selling Partner segmentation, behavior and satisfaction, Amazon operational performance and impact on Amazon customer experience by identifying, developing, and executing analyses, machine learning capabilities and models
* Navigate ambiguity; identify and tackle strategic opportunities and problems we don't even know exist or have not fully defined through data.
* Mentor other team members who are looking to improve their understanding of machine learning and data science
* Implement models that comply with evaluations of the computational demands, accuracy, and reliability of the relevant ETL processes at various stages of production.
Amazon is an electronic commerce and cloud computing company.