Lead Data Analyst

Who you are

• Extensive experience delivering trusted financial and risk data products, with an understanding of Foreign Exchange products, trade lifecycles, revenue, risk and client data
• Expert Structured Query Language skills, strong Python capability and advanced Tableau knowledge, supported by experience delivering controlled, tested and supportable production data products
• Strong interpersonal and communication skills, with the ability to collaborate, build trust and connect business stakeholders with data platform engineering teams
• Experience guiding and coaching a small analytics team while remaining closely involved in delivery and supporting shared outcomes
• Proven use of GitHub Copilot or equivalent Artificial Intelligence-assisted workflows across data analysis, coding, testing, review and documentation
• A committed and responsive approach to data governance, quality, lineage, access controls and collaborative delivery
• Proven ability to leverage AI tools to enhance productivity, optimise workflows to solve business problems, while applying critical judgment to ensure responsible and ethical use of data and AI outputs

What the job involves

• Join FX Data Analytics within Global Foreign Exchange as a hands-on Lead Data Analyst leading two to four analysts
• You will turn complex financial and risk data into trusted datasets, controls and Tableau insights for Sales, Trading, Finance, Risk and Controls - from stakeholder discovery and business rules through SQL and Python delivery and support
• You will modernise legacy flows, lead migrations and use AI-assisted workflows every day
• Lead two to four analysts: set priorities, coach delivery and review analysis and code
• Represent analytics as the senior stakeholder to data platform engineers, translating business needs into clear requirements, priorities, acceptance criteria and outcomes
• Design, build and productionise analytical datasets, controls, management information and Tableau dashboards; own their sources, models, business rules, quality, testing, access, lineage and documentation
• Lead modernisation, migration and decommissioning by mapping dependencies, assessing gaps, prioritising delivery and protecting critical consumers
• Remain hands-on in SQL and Python delivery, releases, incident investigation and performance tuning, embedding review, knowledge-sharing and engineering standards