Design and build AI-powered data pipelines within Databricks
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

Strong experience working with Databricks Lakehouse architecture
Experience designing and maintaining scalable data pipelines
Ability to process and model large-scale analytical datasets
Advanced SQL development
Experience building modular and reusable transformations
Experience with Jinja SQL (dbt or similar frameworks)
Strong data modeling skills for analytics and reporting
Experience integrating LLM APIs (OpenAI, Anthropic, etc.) into data workflows
Hands-on experience using AI for data enrichment, anomaly detection, automated classification
Experience with LangChain, LlamaIndex, or similar frameworks
Exposure to Model Context Protocol (MCP) or similar approaches to connect AI models with external tools and data sources
Experience with GitHub workflows (Nice-to-Have / Medium)
Familiarity with CI/CD pipelines (Jenkins or similar)
Experience working with YAML/YML configuration files

AI Engineer, Data Engineer

Key skills