Join the Amazon Regulatory Intelligence Safety and Risk (RISC) team as a Data Engineer II. This role is crucial for protecting customers by ensuring product safety and compliance. You will design, build, and maintain large-scale data pipelines and infrastructure to support critical data and analytics initiatives.

Our team focuses on a science-first approach, creating tools for selling partners, and innovating to reduce operational costs. This is an opportunity to contribute to scalable data solutions that enhance Amazon's business efficiency and simplify compliance journeys for selling partners worldwide.

We are committed to fostering a work environment that values work-life harmony, continuous learning, and career growth. Our inclusive culture empowers employees to deliver exceptional results.

Key responsibilities include designing and maintaining automated ETL/ELT pipelines using Python, Spark, and AWS services, along with optimizing data warehouse and data lake architectures. You will implement and support reporting and analytics infrastructure, develop high-quality data models and transformations, and build enterprise-scale data security solutions.

Further duties involve maintaining metadata, data catalogs, and user documentation. You'll collaborate with business customers and technical teams to gather requirements, and develop self-service tooling and automation, including GenAI-powered agents. Responsibilities also extend to designing and operating compliance-critical data validation pipelines and monitoring/optimizing compute resource utilization.

Continuously stay updated with emerging technologies, including AI advancements, and integrate them into the existing data ecosystem for ongoing improvement. You will also work on solutions to scale analytics capabilities and automate repetitive engineering tasks.

This role requires a minimum of 3 years of data engineering experience and 4+ years of SQL experience. A strong background in data modeling, warehousing, and building ETL pipelines is essential. Familiarity with orchestration patterns such as event-driven architectures (EventBridge, Step Functions, Lambda) and workload/cost optimization techniques for compute infrastructure is also necessary.

Preferred qualifications include experience with AWS technologies such as Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions. Experience with non-relational databases/data stores and building or operating GenAI-based tooling or agentic workflows is highly desirable.

We are looking for individuals who can collaborate effectively and contribute to a dynamic team environment. A passion for innovation and continuous improvement is key.