Reference Data Business Analyst

Другое

• QRT is a global quantitative and systematic investment manager, operating across all liquid asset classes. We are a data- and technology-driven organization applying scientific methods to investing. Our collaborative culture and focus on innovation enable us to solve complex challenges and deliver high-quality returns for our investors. The newly formed Reference Data Technology Team is building a new reference data system. The team works with stakeholders across Trading, Operations, Compliance and Research to translate business and regulatory requirements into data models, datasets and data quality controls.
• Your future role within QRT
• We are seeking an exceptional Reference Data Business Analyst to join our Reference Data Technology Team. The role is expected to involve the following activities:
• Translate business and regulatory requirements into data entity models and datasets for the new reference data system.
• Work closely with the Data/Platform Architect to ensure business requirements map cleanly onto the technical model.
• Gather and validate requirements directly with domain stakeholders across Trading, Compliance and Research.
• Partner with Trading, Operations and Compliance teams to build automated data quality rules and checks, exception-management workflows and metrics.
• Provide day-to-day support to business, compliance and technology teams as a subject matter expert on data queries and system behaviour.
• Apply expert knowledge of equity reference data, related events, and the lifecycle and processing of corporate actions.
• Support the initial delivery focused on Equities and ETFs and its direct impact on the trading business.
• Produce data dictionaries, entity relationship diagrams and requirements specifications.
• Your present skillset
• Experience producing entity and data models for reference or master data platforms in financial services.
• Deep working knowledge of ETF reference data, including composition and basket data, creation and redemption mechanics, and identifiers.
• Hands-on knowledge of ETF corporate actions processing, including dividends, splits, mergers and delistings.
• Understanding of corporate actions lifecycle stages, timing and effective-date handling, and the downstream impact of processing errors.
• Experience defining corporate actions data quality rules, including the detection of missed or conflicting action records and effective-date validation.
• Strong requirements-gathering skills across multiple stakeholder groups, including Trading, Compliance and Operations.
• Working knowledge of data quality concepts, including completeness, accuracy, timeliness and referential integrity.
• Ability to translate regulatory and business rules into structured, testable data rules.
• Comfortable working directly with technical architects to map business requirements onto a reference data model.
• Strong written documentation skills, including data dictionaries, entity relationship diagrams and requirements specifications.
• Strong database and SQL skills for data interrogation and analysis.
• Desirable to have experience or a willingness to learn in the following areas
• Client and account reference data, including legal entity structures, KYC, account hierarchies and LEIs.
• Master data management concepts, including golden source, survivorship and entity resolution.
• Scoping an MVP and maintaining a firm line on deferred scope.
• Data lineage, metadata cataloguing and associated tooling.
• Data modelling tools, including entity relationship diagramming and data catalogue tools.
• UK and EU financial services regulatory frameworks relevant to reference data, including the LEI regime and KYC/CDD requirements.
• Python experience and knowledge.