Data Engineer II

DESCRIPTION

Amazon Regulatory Intelligence Safety and Risk (RISC) team mission is to protect customers from products that are unsafe, illegal, illegally marketed, controversial or otherwise in violation of Amazon’s policies while enabling our Selling Partners to offer their broadest selection of safe and compliant products. We achieve these objectives worldwide by: (1) taking a science-first approach to offer trustworthy listings to our customers, (2) inventing intuitive and precise tools to simplify our selling partners’ compliance journey and (3) innovating to reduce our cost to serve. The RISC Data Engineering team is seeking an experienced Data Engineer to join our team. In this role, you will be responsible for designing, building, and maintaining large scale robust data pipelines and infrastructure to empower our data and analytics initiatives. You will collaborate closely with tech teams and business stakeholders to understand their requirements and support with scalable data solutions. Join our expert team to build scalable data solutions, improving Amazon business efficiency and simplifying our selling partners' compliance journey. Key job responsibilities 1. Design, develop, and maintain automated ETL/ELT pipelines with monitoring using Python, Spark, SQL, and AWS services such as Redshift, S3, Glue, Lambda 2. Optimize data warehouse and data lake architectures using best practices for DDL, physical and logical table design, data partitioning, compression, and parallelization 3. Implement and support reporting and analytics infrastructure for internal business customers 4. Develop optimized data models and transformations to ensure high-quality, well-structured data for business and analytics applications 5. Develop and maintain enterprise-scale data security solutions including data encryption, database user access controls, logging, and permissions management for data warehouse and data lake implementations 6. Maintain data warehouse and data lake metadata, data catalog, and comprehensive user documentation 7. Collaborate with internal business customers and technical teams to gather, document, and implement requirements for data publishing and consumption via data warehouse, data lake, and analytics solutions 8. Stay current with emerging technologies, tools, and trends (including AI advancements), evaluating and incorporating them into the existing data ecosystem for continuous improvement About the team Who Are We We are a team of engineers building scalable data solutions to improve Amazon business efficiency and simplify our selling partners' compliance journey. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. Mentorship and Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

BASIC QUALIFICATIONS

• 3+ years of data engineering experience
• 4+ years of SQL experience
• Experience with data modeling, warehousing and building ETL pipelines

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)