Key job responsibilities
1. Design, develop, and maintain scalable data pipelines to support AI/ML model development and production deployment.
2. Implement and maintain CI/CD pipelines for the data and AI/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 AI/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.
Experience with data modeling, warehousing and building ETL pipelines
3+ years of data engineering experience
Knowledge of at least two of the following programming languages: Scala, Java, Python, C/C++, or Go
Knowledge of cloud services such as AWS or equivalent
Experience with version control systems and CI/CD pipeline implementation
Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
Experience with training and deploying AI/ML systems to solve large-scale optimizations
Experience working with data analytics
Experience with big data technologies
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