What you will need:- Strong Python development skills with a focus on automation and developer tooling.
- Hands-on experience with AI coding assistants such as GitHub Copilot, Claude Code, Cursor, or similar tools.
- Practical knowledge of agentic AI concepts, including tools, skills, prompts, and multi-step workflows.
- Experience designing and implementing MCP (Model Context Protocol) integrations.
- Understanding of LLM capabilities, limitations, and prompt engineering best practices.
- Familiarity with integrating agents with APIs, databases, and enterprise systems.
- Proficiency with Git and modern software development workflows.
- Experience working with Agile teams and tools such as Jira.
- Strong problem-solving skills and a passion for improving developer productivity.
- Good communication skills and professional proficiency in English.
Nice to have:- Knowledge of data processing tools and standards (dbt, ODCS, ODPS)
,(Design and develop AI agents supporting data engineering workflows., Build agent capabilities directly within modern IDE environments., Automate repetitive data engineering tasks using agentic solutions., Integrate agents with data platforms, pipelines, and developer tools., Create reusable prompts, tools, and workflows for engineering teams., Collaborate with data engineers to identify automation opportunities., Optimize agent performance, reliability, and response quality., Test, validate, and continuously improve agent behavior., Monitor agent usage and implement feedback-driven enhancements., Document agent architectures, best practices, and implementation guidelines.) Requirements: Python, AI, GitHub, Claude Cod, Cursor, Communication skills, dbt, ODCS, ODPS