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Common Data Analyst title with generalist SQL/Tableau requirements increases applicant competition.
Core SQL, BI, and Python skills are transferable, though liquidity finance domain knowledge moderately matters.
Explicit 1–4 years and mandatory advanced SQL plus tooling experience creates moderate filtering.
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Maintain and troubleshoot liquidity risk systems to ensure optimal performance and support liquidity management decision making.
Assist in data analysis, implementation of new methodologies, and development/deployment of proof-of-concept models for liquidity analytics.
Collaborate with technology and cross-functional teams to improve risk management tooling, dashboards, and visualisation using tools like Tableau or Superset.
Bachelor’s degree in Finance, Technology, or a related field from a recognized institution.
1–4 years of relevant experience in data, reporting, or IT-related roles.
Advanced proficiency in SQL and experience in database management, including optimisation of stored procedures; exposure to Python is ideal.
Experience with data visualisation tools such as Tableau or Superset; knowledge of Excel and foundational database concepts.
Has operational experience supporting liquidity risk systems and technical solutions in a finance or data-driven environment.
Comfortable working within cross-functional teams to implement data-driven liquidity risk management solutions.
Strong analytical ability to interpret data and improve risk management tools and processes focused on liquidity analytics.