Amazon Data Engineer II ROW AOP 

China, Jilin, Dehui City 

208697391

• Using live package and truck signals to adjust truck capacities in real-time
• HOTW models for Last Mile Channel Allocation
• Using LLMs to automate analytical processes and insight generation
• Ops research to optimize middle mile truck routes
• Working with global partner science teams to affect Reinforcement Learning based pricing models and estimating Shipments Per Route for $MM savings
• Deep Learning models to synthesize attributes of addresses
• Abuse detection models to reduce network lossesKey job responsibilities
1. Design, develop, and maintain scalable data pipelines to support ML model development and production deployment.
2. Implement and maintain CI/CD pipelines for the data and ML solutions.
3. Collaborate with data scientists and other team members to understand data requirements and implement efficient data processing solutions.
4. Create and manage data warehouses and data lakes, ensuring proper data governance and security measures are in place.
5. Collaborate with product managers and business stakeholders to understand data needs and translate them into technical requirements.
6. Stay current with emerging technologies and best practices in data engineering, and propose innovative solutions to improve data infrastructure and processes for ML models and analytics applications.
7. Participate in code reviews and contribute to the development of best practices for data engineering within the team.

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 3+ years of experience in data engineering or related roles.
- Strong programming skills in languages such as Python, Java, or Scala.
- Expertise in SQL and experience with both relational and NoSQL databases.
- Familiarity with cloud platforms (e.g., AWS) and their services.
- Knowledge of data modeling, data warehousing, and ETL design patterns.
- Experience with version control systems (e.g., Git) and CI/CD pipelines .
- Strong problem-solving skills and attention to detail.
- Excellent communication skills and ability to work in a collaborative team environment.

- Experience working in a scientific or research-oriented environment.
- Familiarity with machine learning workflows and model deployment.
- Experience with Infrastructure as Code (IaC) by tools such as CDK.
- Experience with streaming data processing and real-time analytics.
- Experience with big data technologies (e.g., Hadoop, Spark, Hive).