Techno-functional Business Analyst

About Phi Partners Phi Partners has been a trusted capital markets consultancy for more than 20 years, providing quantitative and technology expertise across front office, pricing and risk. We support more than 80 financial institutions across the buy-side and sell-side through niche capabilities spanning quant, engineering, vendor platforms and cloud infrastructure. Our teams work on complex, real-world problems across models, analytics, applications, data and cloud infrastructure, within an international delivery organisation built around regional hubs and specialist centres of excellence. For people who enjoy technically demanding work in capital markets, Phi offers the opportunity to work closely with expert colleagues and major financial institutions on high-value, business-critical initiatives. About the Programme We are supporting one of the world’s largest institutional investors, a global sovereign wealth fund investing across public and private markets. The opportunity sits within the client’s Public Markets Data team, which supports the investment business across risk data, including counterparty credit risk, market risk, margining and collateral, as well as market data and trade execution. The client is consolidating its data capabilities onto Databricks as an enterprise-level data platform, making this a key area of its broader technology and data strategy. Phi Partners is looking for a Techno-Functional Business Analyst to act as the bridge between the investment business and the data engineering teams. This is not a traditional, analysis-only BA role: the successful candidate will also be expected to work hands-on with the data and the pipelines behind it. The role will initially focus on one of the team’s key areas, with the opportunity to develop broader knowledge across the Public Markets Data function over time. The client understands that candidates may not have deep knowledge of every area from day one and will support the successful candidate in building it. As an example of the work, a front-office or compliance team might ask for a new metric on an existing dashboard, such as a 36-month rolling beta. The Business Analyst would trace where the underlying time-series data comes from and what it represents, work out how the metric should be derived, and specify it so a data engineer can build it directly. Roles and Responsibilities The successful candidate will work at the intersection of investment data, business analysis and technology, helping stakeholders turn complex data requirements into practical solutions. The role requires someone who can investigate problems independently, understand the underlying financial and technical context, and work effectively across business and engineering teams. Key Responsibilities: • Gather and translate requirements from Front Office and business stakeholders into clear technical and data specifications • Analyse datasets, data flows and dependencies, defining source-to-target mappings, transformations, data models and data quality requirements • Work hands-on with Databricks, Spark and SQL to profile data, develop or review pipelines, investigate issues and validate outputs • Create lightweight prototypes where required to help stakeholders visualise and refine reporting or data solutions • Manage a personal Book of Work across multiple smaller workstreams, independently investigating requirements and proposing solutions • Work closely with Data Engineers and business stakeholders throughout delivery, ensuring effective communication between business and technology teams Key Skills Mandatory skills include: • Minimum five years as a Business Analyst or BA/PM, with substantial data engineering experience and delivery on projects in the financial domain • Hands-on Python and PySpark coding experience, ideally on Databricks, is essential • Advanced SQL (complex joins, window functions, reconciliations) for in-depth data analysis • Good understanding of financial markets and investment concepts across buy side and sell side, ideally with exposure to security master, reference data, market data, the trade lifecycle or other investment-related data • High-level understanding of risk modelling and instrument pricing: how an instrument is priced and how risk is measured, without needing quant-level depth • Experience working with structured financial data and data modelling concepts • Comfortable working directly with front-office users and using their terminology • Ability to manage several workstreams in parallel with limited supervision • Strong written and verbal communication skills in English, able to explain technical design to investment professionals and investment concepts to engineers • Bachelor’s degree in IT, Finance, Engineering or a related field Nice to Have Skills: • Domain exposure to trade execution, counterparty credit risk, market risk, or margining and collateral • Experience with the Azure data stack and Azure DevOps • Experience with Power BI or an equivalent BI tool • Databricks certification or an investment qualification such as CFA (any level) or IMC • Previous experience at a sovereign wealth fund, large asset manager or investment bank Next steps This is an opportunity to join a growing capital markets consultancy and work within the data team of one of the world’s largest institutional investors. The role offers close exposure to front-office stakeholders and the chance to build broad knowledge across investment data while staying hands-on technically. If you are interested, please send a copy of your up-to-date CV to [email protected]. We look forward to discussing the role with you in more detail.

Minimum five years as a Business Analyst or BA/PM, with substantial data engineering experience and delivery on projects in the financial domain. Hands-on Python and PySpark coding experience, ideally on Databricks. Advanced SQL (complex joins, window functions, reconciliations) for in-depth data analysis. Good understanding of financial markets and investment concepts across buy side and sell side, ideally with exposure to security master, reference data, market data, the trade lifecycle or other investment-related data. High-level understanding of risk modelling and instrument pricing: how an instrument is priced and how risk is measured, without needing quant-level depth. Experience working with structured financial data and data modelling concepts. Comfortable working directly with front-office users and using their terminology. Ability to manage several workstreams in parallel with limited supervision. Strong written and verbal communication skills in English, able to explain technical design to investment professionals and investment concepts to engineers. Bachelor’s degree in IT, Finance, Engineering or a related field.

Gather and translate requirements from Front Office and business stakeholders into clear technical and data specifications. Analyse datasets, data flows and dependencies, defining source-to-target mappings, transformations, data models and data quality requirements. Work hands-on with Databricks, Spark and SQL to profile data, develop or review pipelines, investigate issues and validate outputs. Create lightweight prototypes where required to help stakeholders visualise and refine reporting or data solutions. Manage a personal Book of Work across multiple smaller workstreams, independently investigating requirements and proposing solutions. Work closely with Data Engineers and business stakeholders throughout delivery, ensuring effective communication between business and technology teams.