The Amazon Marketing team is working on a platform that will provide real-time insights of traffic, sales, deals, and engagement. We are looking for a rock star Data Engineer to build this. At Amazon, understanding customer data is paramount to our success in making it Earth's most measurably effective marketing organization. This cuts across all of the investments we do across various verticals of A.in, Prime, Fashion, Fresh, Pay, etc.
At Amazon, you will be working in one of the world's largest and most complex data environments.
You will be part of a team that will work with the marketing, retail, finance, analytics, machine learning, and technology teams to provide real-time data processing solutions that give Amazon leadership, marketers, and PMs timely, flexible, and structured access to customer insights. The team will be responsible for building this platform end-to-end using the latest AWS technologies and software development principles.
As a Data Engineer, you will be responsible for leading the architecture, design, and development of the data, metrics, and reporting platform for Prime. You will architect and implement new and automated Business Intelligence solutions, including big data and new analytical capabilities that support our Development Engineers, Analysts, and Retail business stakeholders with timely, actionable data, metrics, and reports while satisfying scalability, reliability, accuracy, performance, and budget goals and driving automation and operational efficiencies. You will partner with business leaders to drive strategy and prioritize projects and feature sets. You will also write and review business cases and drive the development process from design to release. In addition, you will provide technical leadership and mentoring for a team of highly capable Data Engineers.
Key Job Responsibilities
1. Own design and execution of end-to-end projects.
2. Own managing IN Marketing core services data infrastructure.
3. Establish key relationships which span Amazon business units and Business Intelligence teams.
4. Implement standardized, automated operational and quality control processes to deliver accurate and timely data and reporting to meet or exceed SLAs.
BASIC QUALIFICATIONS
* 4+ years of data engineering experience.
* 4+ years of SQL experience.
* Experience with data modeling, warehousing, and building ETL pipelines.
* Experience with one or more query languages (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala).
* Experience with one or more scripting languages (e.g., Python, KornShell).
PREFERRED QUALIFICATIONS
* Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions.
* Experience with non-relational databases/data stores (object storage, document or key-value stores, graph databases, column-family databases).
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