The Opportunity
We are looking for a Technical Data Analyst to help build the data foundations that support modern, AI-enabled applications within a global financial services environment.
This is an exciting opportunity for someone who combines strong data engineering and data modelling skills with an interest in modern AI technologies. You will work across data, engineering, architecture and business teams to turn complex requirements into trusted, scalable and reusable data solutions.
You'll play an important role in making enterprise and investment data accessible, well-structured and fit for use by next-generation applications, including AI-powered tools and agents.
What You'll Do
Data Modelling & Integration
- Design and develop AI-ready data models for enterprise and investment data.
- Develop data transformations and integration patterns connecting enterprise data sources with curated datasets.
- Create scalable, reusable data capabilities that can support multiple applications and use cases.
- Design data solutions with maintainability, performance and future reuse in mind.
AI & Data Enablement
- Work with data strategy and engineering teams to identify, shape and make data readily available for AI-enabled applications.
- Support modern AI data patterns including RAG, embeddings and Vector Search
- Work with both structured and unstructured data to support AI applications and agent-based solutions.
- Use AI-assisted development and rapid prototyping techniques to accelerate delivery while ensuring solutions can be robustly productionised.
Data Quality & Governance
- Build data quality, governance and lineage into data solutions.
- Ensure data is trusted, controlled, traceable and suitable for use by business and AI applications.
- Help establish reusable data foundations and standards across the technology environment.
Collaboration
- Work closely with AI engineers, data specialists, architects and business stakeholders.
- Translate business and application requirements into clear, practical data requirements and solutions.
- Contribute to an environment where experimentation and innovation are balanced with appropriate governance, security and risk controls.
What We're Looking For
You'll have a strong background in enterprise data and a genuine interest in making data accessible, trusted and usable by modern applications.
Essential Experience
- Practical experience with Snowflake, including enterprise datasets, data modelling, transformations and curated data layers.
- Experience designing and implementing ETL/ELT processes and data pipelines across multiple enterprise data sources.
- Good understanding of data modelling, data quality, lineage and governance.
- Practical experience using SQL and/or Python for data analysis, transformation and automation.
- Experience collaborating with data, engineering and architecture teams to translate business or application requirements into practical data solutions.
Desirable Experience
Experience in one or more of the following would be advantageous:
- Snowflake Cortex and AI-enabled data solutions.
- AWS data and analytics capabilities.
- AI data pipelines, RAG, embeddings and vector search.
- Integration of structured and unstructured data.
- APIs and enterprise data integration patterns.
- AI-assisted development tools and techniques.
- Asset Management, Investment Management or Financial Services
