Data Analyst II

What you'll be doing

• This is not a traditional reporting role. You'll own and evolve the Sigma analytics platform sitting on top of our Snowflake data environment and work closely with Treasury leadership to ensure critical insights are always available, accurate and decision-ready. The Data Analyst will work as the bridge between technical teams to translate business questions to data requirements. Understand the business processes and how data flows into the warehouse. Be involved in the design of new processes and ensure the design caters for data needs at the end of projects with little to no data rework needed.

You wil

• Own the analytics layer
• Build and maintain Sigma dashboards, data models and reporting solutions supporting ALCO, Exco and Board-level decision-making.
• Turn complex data into clear insight
• Translate Treasury, liquidity and capital requirements into usable data products that shape strategy and planning.
• Drive smarter decision-making
• Design KPIs, dashboards, scenario analyses and self-service tools that enable faster, data-driven decisions across technical and non-technical stakeholders.
• Act as the bridge between business and data
• Translate business questions into data requirements and ensure reporting solutions are built with the end in mind.
• Improve and automate how we work
• Identify opportunities to streamline reporting, reduce manual effort and use AI/modern tooling to improve productivity and efficiency.
• Partner across teams
• Work closely with Treasury, Finance, Risk, Data Engineering and Analytics teams to deliver high-quality, scalable solutions.
• What we're looking for

Minimum requirements • Relevant degree in Data, Analytics, Finance, or a related field • Minimum of 5 years' Experience in data analysis, BI engineering or analytics platforms • Strong SQL skills and experience working with large datasets • Experience with BI tools such as Sigma, Power BI, Tableau or similar • Ability to communicate insights clearly to non-technical stakeholders • Minimum of 5 years' Experience delivering data-driven insights in a business environment

What will set you apart • Experience working on cloud data platforms e.g. Snowflake • Exposure to Treasury, banking or financial services data • Experience building data models, dashboards and automated workflows • Understanding of AI/GenAI use cases in analytics • Experience working with or interpreting Python/R/Excel-based models • Proven track record of influencing decisions through data at a senior level

Qualifications Minimum

• Bachelor's Degree in Analytical/Data/Technical or Other

Qualifications Ideal or Preferred

• Honours Degree in Analytical/Data/Technical or Other

Knowledge

• Advanced proficiency in writing complex SQL, optimising query performance, and working with large datasets on a cloud warehouse Snowflake preferred.
• Strong proficiency in building advanced, governed visualisations, dashboards and data models in Sigma or Tableau / Power BI / Looker / similar.
• Solid understanding of cloud data warehouse architecture, data modelling and semantic layers data layer, scenarios, lineage — ideally Snowflake.
• Understanding of analytics workflow orchestration, automation and data governance — version control, approvals, audit trails and lineage.
• Practical understanding of AI/GenAI applied to analytics — semantic layers, AI-assisted workflow and dashboard design, and automation of analytics processes.
• Ability to read and interpret existing Python, R or Excel models in order to port their logic and outputs into Sigma + Snowflake.
• Expertise in advanced Excel including macros/VBA sufficient to interpret and migrate existing Excel-based models.
• Awareness of Treasury / ALM concepts IRRBB, NII/EVE, LCR/NSFR, FTP, capital planning, stress testing and regulatory artefacts LAS, ICAAP, ILAAP, CSST, Recovery Plan is advantageous — domain depth is provided by the quants and ALM specialists the role supports

Skills

• Analytical Skills
• Communications Skills
• Problem solving skills
• Project Management Skills Methodolgy Specific