Data Business Analyst & AI Engineer
Summary
Hybrid business analyst and AI engineer: elicits requirements, maps and validates data, and enhances Qlik dashboards for sustainability, portfolio and investment-data applications, while building generative-AI solutions (RAG, AI agents, document intelligence) using SQL, Python and Snowflake.
The Data Business Analyst and AI Engineer will bridge business requirements, enterprise data and AI-enabled delivery. The role will work directly with business users and technology teams to understand reporting and operational needs, analyze complex datasets, define functional and data requirements, and deliver reliable analytical and AI solutions.
The candidate will support sustainability, portfolio and investment-data applications; perform data mapping, reconciliation and validation; enhance Qlik dashboards; and contribute to AI use cases such as natural-language data access, document intelligence and configurable agents. Responsibilities include requirements workshops, user stories, solution analysis, prototyping, testing, release support, production issue investigation and documentation.
The role requires 5-10+ years of relevant experience, strong SQL and business-analysis capability, working knowledge of Qlik and Snowflake, and practical experience with Python and modern generative-AI patterns. Experience in investment management, sustainability data and regulated enterprise environments is advantageous.
Skill requirements:
- 5-10+ years of relevant experience in a similar role
- Business analysis, requirements elicitation, user stories and functional specifications
- Strong SQL, data profiling, mapping, reconciliation and data validation
- Qlik reporting, dashboard analysis and analytical application support
- Python and Snowflake for data and AI solution development
- Generative AI, prompt engineering, retrieval-augmented generation, AI agents and document intelligence