The AOP (Analytics Operations and Programs) team is responsible for creating core analytics, insight generation and science capabilities for ROW Ops. We develop scalable analytics applications, AI/ML products and research models to optimize operation processes. You will work with Product Managers, Data Engineers, Data Scientists, Research Scientists, Applied Scientists and Business Intelligence Engineers using rigorous quantitative approaches to ensure high quality data/science products for our customers around the world. As a Data Engineer, you will play a crucial role in supporting the team by creating and maintaining the data infrastructure necessary for the advanced analytics and machine learning solutions.
Our team solves a broad range of problems that can be scaled across ROW (Rest of the World including countries like India, Australia, Singapore, MENA and LATAM). Here is a glimpse of the problems that this team deals with on a regular basis:
• 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 losses
Key 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.
About the team
The AOP (Analytics Operations and Programs) team is responsible for creating core analytics, insight generation and science capabilities for ROW Ops. We develop scalable analytics applications, AI/ML products and research models to optimize operation processes. You will work with Product Managers, Data Scientists, Research Scientists, Applied Scientists and Business Intelligence Engineers using rigorous quantitative approaches to ensure high quality data/science products for our customers around the world.- Bachelor's degree or above in computer science, computer engineering, or related field, or Master's degree
- 3+ years of data engineering experience
- Knowledge of at least two of the following programming languages: Scala, Java, Python, C/C++, or Go
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
- Knowledge of cloud services such as AWS or equivalent
- Knowledge of data warehouse technical architecture, infrastructure components, ETL and reporting/analytic tools and environments
- Experience with version control systems and CI/CD pipeline implementation
- Experience in complex problem solving, and working in a tight schedule environment
- Experience working in a collaborative team environment to deliver high-quality design solutions- Experience in industry, consulting, government or academic research
- Experience with training and deploying machine learning systems to solve large-scale optimizations, or experience in agile/scrum or related collaborative workflow
- Experience with automation and any version control tools, or experience in managing and troublshooting network and experience in Kafka
- Experience working with data and analytics
- Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc.
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