Business System Analyst

Key Responsibilities:

• Capital markets (Equity, Fixed Income, Derivatives)

• Asset management / investment lifecycle

• Portfolio management concepts

• Asset allocation and risk-adjusted returns

• Investment valuation techniques

• CFA (Chartered Financial Analyst) – Required or Progressing

• Financial modeling (Excel, Python preferred) • Data analysis and reporting tools (SQL, Power BI, Tableau)

• Experience with financial platforms or data sources (Bloomberg, FactSet, etc.)

• Requirement gathering and documentation

• Process mapping and workflow design

• Strong analytical and problem-solving skills

• Own end to end delivery and support of financial services data products, from requirement intake through production support, ensuring stability, accuracy, and timeliness.

• Act as the primary Technical BSA for BAU and production data issues, taking accountability for root cause analysis, remediation, and prevention of recurring issues.

• Partner with business stakeholders to translate financial domain business needs into clear, actionable functional and technical specifications, including data mappings, transformations, and validation rules.

• Work closely with data engineering and technology teams to analyze existing data logic, review SQL and code, and validate that implementations align with business intent.

• Proactively monitor and assess data quality, identify issues early, and drive resolution through to completion rather than simple escalation.

• Support Agile delivery by contributing to backlog refinement, sprint planning, story breakdown, acceptance criteria, and release readiness.

• Collaborate with Front Office, Risk, Operations, and downstream consumers to clarify requirements, resolve data questions, and ensure shared understanding of outputs and impacts. • Ensure data solutions meet production grade standards, including stability, accuracy, traceability, auditability, and operational resilience.

• Continuously improve BAU processes, controls, and documentation, reducing operational risk and improving transparency and efficiency.

• Proactively identify opportunities for process optimisation, automation, and improved data controls, incorporating best practices across financial services data delivery.

• Your Profile Essential skills/knowledge/experience: • Bachelor’s degree in computer science, Information Systems, Data Analytics, Business Information Systems, or a related discipline. • 5+ years proven experience in a Technical Business Analyst, Business Systems Analyst, Data Analyst, or similar role within financial services / capital markets. • Hands on experience supporting investment, trading, risk, operations, or regulatory reporting data platforms in a production environment. • Experience working with industry standard investment or portfolio management platforms. • Strong understanding of financial services data domains, with the ability to engage confidently with Front Office, Risk, Operations, and Technology stakeholders without heavy translation layers. • Demonstrated experience acting as a primary BA/BSA for BAU and production critical issues, with clear ownership from investigation through resolution. • Strong analytical and problem solving skills, particularly in the context of complex data, business logic, and operational issues. • Excellent communication skills, with the ability to explain complex data concepts clearly to both technical and non technical audiences. • Ability to manage multiple priorities and deliver outcomes in a fast paced, Agile delivery environment, with a strong sense of ownership and accountability. Technical Skills & Experience: •        Strong SQL expertise, including the ability to: o        write, review, and optimize complex queries, o        perform independent data analysis and validation o        debug and investigate production data issues •        Hands on experience working with relational data models and enterprise data platforms (e.g. Microsoft SQL Server). •        Ability to read existing code (e.g. SQL, Python, Java) to extract, decompose, and validate underlying business logic. •        Solid understanding of core data concepts, including: o        Source to target mappings o        Data transformations and enrichment o        Historical vs “as of” data handling o        Data quality, reconciliation, and control frameworks