Senior Data Analyst

6 Month Daily Rate Contract

Dublin Hybrid

Requirements:

• Bachelor’s or Master’s degree in Data Analytics, or a related field.

• Proven experience as a Lead Data Analyst / BI Developer or in a similar role.

• Wide ranging experience with data visualisation, reporting, business intelligence, UI/UX design, KPI metric definition, UAT, and data manipulation.

• Solid experience of BI tools (e.g., Power BI, Tableau, Quicksight, SAS Viya)

• Excellent knowledge and experience of SQL.

• Strong problem-solving skills and attention to detail.

• Strong communication skills and the ability to present complex data in an intuitive format to leaders within an organisation.

• A minimum of 5 years’ relevant experience in a similar role.

• Experience in the banking or financial services industry.

• Skills in Advanced Analytics.

Responsibilities:

• Lead the design, development and maintenance of analytics, semantic data models and BI solutions, including visualisations, reports and dashboards, from proof of value through to industrialisation, enabling complex datasets to be represented through trusted and accessible business insights.

• Guide the delivery of enterprise BI dashboards, performance scorecards and reusable semantic models, ensuring consistent KPI definitions, business terminology, calculation logic, version control and reporting standards.

• Lead the end-to-end Analytics and BI lifecycle, implementing appropriate delivery methodologies, governance controls, testing standards and change management processes.

• Define and oversee roles and responsibilities for the semantic layer, working with business owners, data stewards, data engineering, architecture and analytics teams to establish clear ownership of metrics, business rules, metadata, data quality and access.

• Drive collaboration with business analysts and end-user groups to understand their analytical, visualisation and AI-enabled insight needs, providing best-practice advice and recommending solutions that deliver the best business outcome.

• Guide the formulation and implementation of BI and semantic layer governance, including metric certification, business glossary alignment, model reuse, access controls, visualisation standards and development best practices.

• Support the optimisation of BI tools, semantic models and delivery processes for efficiency, performance and scalability, ensuring consistent adherence to agreed standards across the data analytics team.

• Enable the responsible use of AI and conversational analytics by ensuring trusted data, governed business definitions and approved metrics are available to support AI agents, Copilot and natural-language querying.

• Provide subject matter expertise in design, governance and delivery forums, ensuring that BI, semantic layer and AI-enabled solutions are aligned with business requirements, enterprise architecture and data governance standards.

• Establish appropriate controls for AI-generated insights, including data access, traceability, validation, human oversight and the monitoring of solution quality and business adoption.

• Coach and mentor less experienced team members in semantic modelling, BI development, data visualisation and the responsible use of AI-enabled analytics, including during hyper-care and project handover.

• Stay abreast of emerging BI, semantic modelling and AI technologies and trends, assessing their relevance and recommending improvements to existing analytics capabilities and solutions.