Senior Investment Data Specialist

Job Title

Department

Overview of Department

The Investment Projects and Improvements team support colleagues in the Investment Department to improve efficiency, reduce risk, and implement changes to cope with changing client or regulatory requirements. A key part of this is supporting the development of our investment strategies and the capabilities we offer clients. The team's main focus is to reduce the burden on investment staff from excessive non-investment related activities such as project work or committee membership.

Purpose of Role

Responsibilities

• Drive the design and delivery of high-quality Investment Data products and act as domain owner for those products in line with our data governance framework, sharing detailed, investment-specific data knowledge.
• Work closely with investment teams to understand how data is consumed and translate their requirements into appropriate data products and features.
• Design practical, reusable data models and semantic structures that support multiple consumption patterns.
• Ensure data products have clear definitions, appropriate data-quality controls, lineage and documentation.
• Contribute to the evolution of the Investment Data platform, including engineering standards, modelling patterns and target architecture.
• Help define how trusted investment data is exposed through BI, analytical, application and AI-enabled channels.
• Work collaboratively with Data Engineers, Data Analysts, Data Solutions Analysts, architecture colleagues and other technology specialists.
• Identify, evaluate and help onboard new traditional and alternative datasets, assessing quality, coverage, methodology, long-term value, cost and compliance considerations.

What success looks like:

• Trusted investment data: Investment teams have access to accurate, reliable and well-governed data products that support effective investment analysis and decision making.
• Reusable data products: Investment requirements are translated into well-designed data models and products that are understandable, reusable and able to support multiple consumption patterns.
• Strong data quality: Effective controls, validation and monitoring identify data issues early, with clear definitions, lineage and documentation supporting confidence in the data.
• Effective investment and technology partnership: Investment professionals and technical teams work effectively together, with complex investment requirements translated into practical data solutions.
• Future-ready capability: The Investment Data platform and its products continue to evolve, making trusted data available effectively through analytical, application and emerging AI-enabled channels.

Your knowledge and experience:

This is a broad role spanning investment knowledge, data and technology, and we don't expect candidates to bring deep expertise across every area listed below. You'll likely bring particular strengths in some areas and opportunities to develop in others. We're interested in the overall depth and relevance of your experience and your ability to operate effectively across these disciplines.

• Deep, practical knowledge of investment data and how it supports the investment lifecycle, including areas such as instruments, research, portfolios, holdings, valuations, trading, benchmarks, performance, risk and company fundamentals and estimates.
• Experience working within, embedded with or directly supporting a systematic or quantitative investment or research team at an asset manager, hedge fund, bank or specialist provider.
• Experience in a data engineering, data analytics, quantitative, investment data or similar data-focused role, including designing, building or supporting analytical data products or reusable datasets.
• Strong Python (including pandas and NumPy) and SQL skills, alongside experience with version control, testing practices and building data-quality, validation and monitoring workflows.
• Strong practical understanding of data modelling, data products, pipelines and semantic models, including data governance, metadata, lineage, quality and entitlement considerations.
• Experience with modern cloud data platforms and analytical architectures, with the ability to understand complex data flows, dependencies and existing platform designs. Snowflake knowledge and experience is highly desirable, with experience of platforms such as Databricks also relevant.
• Hands-on experience with major investment data vendors, for example Bloomberg, LSEG, FactSet, S&P Global or MSCI, including their data models and the ability to evaluate datasets objectively.
• Experience delivering data for reporting, analytics or applications, including experience with Power BI, Microsoft Fabric, Streamlit, APIs or similar technologies, alongside an understanding of emerging approaches to data consumption through LLMs, AI applications and agent/MCP-based services.
• Ability to translate investment business requirements into practical data solutions and communicate effectively with both investment professionals and technical specialists.
• Ability to balance short-term delivery with longer-term platform and strategic considerations.

The type of candidate that we're looking for

We're looking for someone who combines strong investment domain knowledge with credible technical or quantitative capability. You'll be comfortable moving between conversations with investment professionals and detailed discussions about data, models and technology, translating complex requirements into practical solutions. You'll be pragmatic and product-oriented, with a focus on creating data products that are understandable, reusable and sustainable rather than solving individual requirements in isolation. You'll enjoy working hands-on with complex data while also thinking about how the Investment Data platform, its architecture and the ways in which data is consumed should evolve over time. You'll bring curiosity and sound judgement to new datasets, technologies and ways of working, balancing immediate delivery with longer-term value, quality and sustainability. You don't need equal depth across investment expertise, data engineering and quantitative capability, but you'll demonstrate strength across at least two of these areas and the ability and appetite to develop in the third.

Critical skills

• Data literacy
• Adaptability
• Systems thinking
• Enabling others
• Digital effectiveness (including AI)

Closing Date

Should you choose to use AI tools to support your application, we ask that you do this thoughtfully. We encourage you to ensure your application reflects your own voice, experience, and motivations. We value authenticity and want to understand your individual strengths and perspectives.

At Baillie Gifford, we are committed to fostering an inclusive and respectful culture in which each of our colleagues can thrive and develop. We believe that our clients are best served by a diverse workforce with the experiences, ideas and perspectives that this brings.

If you are currently working at Baillie Gifford as an employee or contractor please apply to this job from the firm's Workday internal career site.