Data Analyst

A leading financial services organisation is seeking an experienced Data Analyst to join a major asset intelligence and balance sheet modernisation programme.

You will help create a trusted, facility-level view of the organisation’s commercial lending portfolio by bringing together loan, exposure, risk and financial data from multiple systems. This data will support portfolio forecasting, in-life management and forward-looking balance sheet decisions.

This is a hands-on role requiring strong SQL skills, commercial lending knowledge and the curiosity to investigate complex or lightly documented datasets. You will work closely with business and technical subject-matter experts to establish how data connects, resolve inconsistencies and translate findings into clear data rules and requirements. Key responsibilities

• Use SQL to extract, profile, join, reconcile and analyse commercial lending and asset data.
• Investigate data gaps, inconsistencies and reconciliation differences across multiple source systems.
• Trace issues back to source definitions, business rules and system-specific nuances.
• Work with lending, asset finance, credit risk, treasury and data specialists to understand the operational meaning of data.
• Document data lineage, definitions, transformation rules and migration paths.
• Translate business questions into functional data requirements and practical data models.
• Support the development of facility-level datasets covering balances, limits, product dimensions and credit-risk measures.
• Contribute to daily stand-ups, collaborative problem-solving and documentation within an Agile delivery team.

• Strong SQL skills, including complex joins, data-quality analysis and reconciliations.
• Hands-on data analysis experience within financial services or a similarly complex environment.
• Practical knowledge of commercial or corporate lending data, such as:
• C&I lending
• Loan booking
• Credit risk
• Lending or asset portfolios
• experience combining data from multiple systems where definitions or documentation may be incomplete.
• The ability to understand the financial and risk meaning of data, not solely its technical structure.
• Strong stakeholder engagement skills, with the confidence to identify subject-matter experts, ask focused questions and clearly document outcomes.
• A curious, persistent and pragmatic approach to investigating data issues.

Desirable experience

• Knowledge of commercial lending products and pricing structures, including base-rate and risk-free-rate lending.
• Understanding of credit-risk and portfolio measures, including PD, EAD, LGD and RWA.
• experience with AWS data services, particularly Athena, and/or Snowflake.
• Knowledge of dimensional modelling, fact tables and standardised data definitions.
• Exposure to portfolio forecasting or predictive modelling.
• experience with Amazon QuickSight or other business-intelligence tools.

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