Responsibilities
- Design and deploy intelligent agents capable of natural language processing for generating, enriching, and reasoning over data within Databricks environments
- Create natural language query interfaces that enable users to interact with data warehouses using everyday language
- Incorporate large language models into data processing pipelines to enhance automation and decision-making capabilities
- Build robust, scalable data architectures that serve both analytical reporting and machine learning applications
- Develop advanced AI-powered features including anomaly identification and intelligent data augmentation
- Work cross-functionally with data science, analytics, and engineering teams to strengthen data accuracy and consistency
- Improve efficiency and scalability of data and artificial intelligence workflows across distributed systems
- Implement continuous integration and continuous delivery practices to streamline deployment processes
- Maintain high standards for data integrity, lineage tracking, and long-term pipeline maintainability
Responsibilities
- Architect AI Agents: Build and deploy agents that can perform NLP-based data generation, automated data enrichment, and complex data reasoning within Databricks.
- Natural Language Interfaces: Develop "Chat with your Data" features, allowing stakeholders to query the data warehouse using natural language.
- Integrate LLMs into data workflows for automation and intelligence
- Develop scalable data models to support analytics and AI use cases
- Implement AI-driven enhancements such as anomaly detection and data enrichment
- Collaborate with data, analytics, and engineering teams to improve data reliability
- Optimize performance and scalability of data and AI workflows
- Support automation through CI/CD practices
- Ensure data quality, traceability, and maintainability across pipelines
