Technical Data Analyst

355 FIL Transaction Services Ltd; Dublin; On-site; EUR 70,000 - 110,000; Full time

Job summary

Fidelity International is seeking a Technical Data Analyst for the Asset Management Platforms team in Dublin, Ireland. You will bridge Portfolio Management Tooling with enterprise data, enabling AI-enabled portfolio management tools with trusted, well-structured data.

You will work with Snowflake and modern AI data patterns, contributing to scalable data models, data governance, and production-ready data solutions across Europe and Asia.

Qualifications

• Practical experience with Snowflake, including enterprise datasets, data modelling, transformations and curated data layers.
• Experience designing and implementing ETL/ELT processes and data pipelines integrating data from multiple enterprise sources.
• Good understanding of data modelling, data quality, lineage and governance with a focus on creating trusted and reusable datasets.
• Practical experience using SQL and/or Python for data analysis, transformation and automation.

Responsibilities

• Data Modelling & Integration Design and develop AI-ready data models for enterprise and investment data used by AI applications, agents and front-office portfolio management tooling.
• Develop data transformations and integration patterns that connect enterprise data sources and curated datasets with the needs of AI applications.
• Design for scalability and reuse, ensuring common data capabilities can support multiple portfolio management tools and AI use cases.
• AI & Data Enablement Work closely with the FIL Data Strategy team and its Snowflake implementation to identify, shape and make the data required by AI-developed portfolio management tools readily available for consumption.
• Support modern AI data patterns, including RAG, embeddings, vector search and the integration of structured and unstructured data.
• Use AI-assisted development and rapid prototyping to accelerate delivery while ensuring successful data solutions can be productionised in a robust and maintainable way.
• Data Quality & Governance Embed data quality, governance and lineage into data solutions, ensuring AI applications have access to trusted, controlled and traceable data.
• Collaboration Collaborate with AI engineers, investment stakeholders, Data Strategy and architects to translate business and application needs into practical data requirements and solutions.

Skills

Snowflake

Data modelling

ETL/ELT

SQL

Python

Data governance

Tools

Snowflake Cortex

AWS

Job description

About the Opportunity

Job Type: Permanent Application Deadline: 17 November 2026

Job Description Title Technical Data Analyst Department Asset Management Platform Location Dublin, Ireland Level 6

About Fidelity International Fidelity International offers world class investment solutions and retirement expertise. As a privately owned, independent company, investment is our only business. We are driven by the needs of our clients, not by shareholders. Our vision is to deliver innovative client solutions for a better future. Our people are passionate, engaged, smart and curious, and we give them the independence and the confidence to make a difference. While we take pride in the excellence of our investment solutions and client service, we know we can always do better. We are honest, respectful and make tough calls, challenging the status quo to achieve better outcomes through innovation. Above all else, we always put our clients first.

About Fidelity International Fidelity International offers world class investment solutions and retirement expertise. As a privately owned, independent company, investment is our only business. We are driven by the needs of our clients, not by shareholders. Our vision is to deliver innovative client solutions for a better future. Our people are passionate, engaged, smart and curious, and we give them the independence and the confidence to make a difference. While we take pride in the excellence of our investment solutions and client service, we know we can always do better. We are honest, respectful and make tough calls, challenging the status quo to achieve better outcomes through innovation. Above all else, we always put our clients first.

About your team

Asset Management Platforms (AMP) is responsible for the design, engineering and delivery of technology solutions that support Fidelity's global Asset Management business. We partner with Investment Management, Asset Management Operations and Distribution teams across Europe and Asia to deliver modern platforms that enable investment professionals to make better investment decisions and improve client outcomes. The Portfolio Management Tooling team develops and supports the technology ecosystem used by Portfolio Managers, Investment Directors, Quantitative Researchers and Investment Specialists across multiple investment capabilities, including Multi-Asset, Systematic Investing, Fixed Income and Equities. Our platforms underpin critical investment processes including research, portfolio construction, analytics, order generation, execution management and investment risk. As Artificial Intelligence increasingly changes how portfolio management tools are developed, access to trusted, well-structured and governed enterprise data becomes critical.

Asset Management Platforms (AMP) is responsible for the design, engineering and delivery of technology solutions that support Fidelity's global Asset Management business. We partner with Investment Management, Asset Management Operations and Distribution teams across Europe and Asia to deliver modern platforms that enable investment professionals to make better investment decisions and improve client outcomes. The Portfolio Management Tooling team develops and supports the technology ecosystem used by Portfolio Managers, Investment Directors, Quantitative Researchers and Investment Specialists across multiple investment capabilities, including Multi-Asset, Systematic Investing, Fixed Income and Equities. Our platforms underpin critical investment processes including research, portfolio construction, analytics, order generation, execution management and investment risk. As Artificial Intelligence increasingly changes how portfolio management tools are developed, access to trusted, well-structured and governed enterprise data becomes critical.

About your role

The Technical Data Analyst will provide the bridge between Portfolio Management Tooling and FIL's enterprise data capabilities, working closely with the Data Strategy team to make trusted, well-structured data available to AI-developed portfolio management tools. You will combine strong data engineering and modelling knowledge with an understanding of modern AI data patterns, helping translate application and investment requirements into scalable, reusable data solutions.

Key Responsibilities

• Data Modelling & Integration Design and develop AI-ready data models for enterprise and investment data used by AI applications, agents and front-office portfolio management tooling.
• Develop data transformations and integration patterns that connect enterprise data sources and curated datasets with the needs of AI applications.
• Design for scalability and reuse, ensuring common data capabilities can support multiple portfolio management tools and AI use cases.
• AI & Data Enablement Work closely with the FIL Data Strategy team and its Snowflake implementation to identify, shape and make the data required by AI-developed portfolio management tools readily available for consumption.
• Support modern AI data patterns, including RAG, embeddings, vector search and the integration of structured and unstructured data.
• Use AI-assisted development and rapid prototyping to accelerate delivery while ensuring successful data solutions can be productionised in a robust and maintainable way.
• Data Quality & Governance Embed data quality, governance and lineage into data solutions, ensuring AI applications have access to trusted, controlled and traceable data.
• Collaboration Collaborate with AI engineers, investment stakeholders, Data Strategy and architects to translate business and application needs into practical data requirements and solutions.

About you

You are a Technical Data Analyst with a strong background in enterprise data and a passion for making data accessible, trusted and usable by modern applications. You enjoy working across business, data and engineering teams and are interested in how Snowflake and modern AI data patterns can provide the foundations for AI-enabled portfolio management solutions.

Core 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 integrating data from multiple enterprise sources.
• Good understanding of data modelling, data quality, lineage and governance with a focus on creating trusted and reusable datasets.
• Practical experience using SQL and/or Python for data analysis, transformation and automation.
• Experience working collaboratively with data, engineering and architecture teams to translate application and business requirements into practical data solutions.

Useful Additional Experience

• Snowflake Cortex and its use in AI-enabled data solutions.
• AWS data and analytics capabilities and integration with enterprise data platforms.
• AI data pipelines, RAG, embeddings and vector search.
• Integration of structured and unstructured data for AI applications and agent-based solutions.
• APIs and enterprise data integration patterns.
• AI-assisted development tools and techniques.
• Experience within Asset Management, Investment Management or Financial Services is desirable but not essential.

Personal Attributes

Passionate about data, technology and the opportunities created by AI, with curiosity about emerging data and AI technologies.

Strong analytical and problem-solving skills, with the ability to understand complex data landscapes and identify practical solutions.

Collaborative and comfortable working across business, data engineering and architecture teams.

Pragmatic and delivery-focused, able to move quickly from analysis and prototyping through to robust, production-ready solutions.

Comfortable working in an evolving environment, taking ownership and working through ambiguity.

Able to balance rapid innovation with appropriate data governance, security and risk controls.