Senior Data Analyst

Ivernia Insurance Ltd; Dublin; On-site; EUR 55,000 - 75,000; Full time

Job summary

Ivernia Insurance Ltd. in Dublin is looking for a Data Analyst to improve their centralized data lake and provide insights for decision making. This role involves managing performance monitoring, data analysis, and enhancing reporting accuracy.

The ideal candidate has over 5 years of experience with data platforms, strong Python and SQL skills, and a solid understanding of relational databases. You will work closely with stakeholders to ensure data is trustworthy and actionable.

Qualifications

• 5+ years experience working with data lakes, warehousing, or data platforms.
• Strong analytical skills and ability to interpret data clearly.
• Experience in personal lines insurance or MGA environment is a plus.

Responsibilities

• Own and enhance the centralized data lake for reporting and analytics.
• Analyse business performance and identify trends.
• Build and maintain management information dashboards.

Skills

Strong Python and/or SQL skills

Advanced Excel skills

Strong analytical and problem solving skills

Solid understanding of data structures and relational databases

Experience with BI tools

Comfortable working with large datasets

Tools

Python

SQL

Power BI

Tableau

Job description

Ivernia Insurance is a specialist personal lines Managing General Agent operating across Motor, Home and Commercial Motor. The business partners closely with insurer capacity providers and operates under delegated authority, with a strong focus on underwriting discipline, pricing integrity and controlled growth.

As the business scales, there is a clear need to strengthen data, MI, and performance insight to ensure growth is profitable, controlled, and aligned with portfolio and capacity expectations.

The Opportunity

The Data Analyst is responsible for turning data into clear, reliable insight to support decision making across the business. The role focuses on management information, performance monitoring, analysis of trends and drivers and building confidence in the quality and consistency of reported data.

A core element of the role is the enhancement, governance and ongoing ownership of an existing centralised data lake, which acts as the organisation’s single source of truth. The role will improve structure, data quality, documentation and usability, ensuring the data lake effectively integrates information across the business to support consistent reporting and analysis over time.

This is a hands on role with a strong emphasis on business understanding, clear communication and practical analysis rather than advanced modelling.

Key Responsibilities

Master Data Lake and Single Source of Truth

• Own and enhance the existing centralised data lake to support reporting, analytics and MI
• Review and improve current data structures, schemas and metric definitions to address gaps and inconsistencies
• Ingest, structure and harmonise data from multiple source systems
• Define core data entities, schemas and metric definitions to ensure consistency
• Implement data refresh logic, validation checks and reconciliation controls
• Improve documentation covering data lineage, definitions and business logic to strengthen trust and usability

Data Analysis and Insight

• Analyse business performance across products, schemes, channels and partners
• Identify trends, movements and drivers in key metrics
• Support deep dive analysis to explain performance changes
• Translate data into clear, concise insights for non technical stakeholders

Management Information and Reporting

• Build, maintain and enhance management information dashboards and reports
• Ensure MI is accurate, timely and consistent
• Develop standard performance packs for senior management and external stakeholders where required
• Support ad hoc reporting requests with quick turnaround

Data Quality and Governance

• Validate data inputs and highlight data quality issues
• Work with business users and technical teams to resolve data gaps or inconsistencies
• Own and contribute to the development of a single source of truth for reporting
• Document definitions, assumptions and logic used in reporting

Stakeholder Engagement

• Work closely with underwriting, pricing, operations, finance and distribution teams
• Understand business questions and translate them into analytical outputs
• Present findings clearly and confidently, both written and verbally

Required Skills and Experience

Technical skills

• 5+ years experience working with data lakes, data warehouses or centralised data platforms
• Strong Python and/or SQL skills
• Advanced Excel skills
• Solid understanding of data structures and relational databases
• Comfortable working with large datasets
• Experience with BI tools

Analytical Capability

• Strong analytical and problem solving skills
• Ability to interpret data and explain results clearly
• Good grasp of descriptive statistics
• High attention to detail

Advantageous

• Prior experience in personal lines insurance or MGA environment
• Prior experience in both Python and SQL
• Prior experience in both Power BI and Tableau
• Prior experience in WTW’s Radar suite

Personal Attributes

• Strong ownership and accountability
• Comfortable working independently while collaborating closely with others
• Able to prioritise and manage competing demands
• Curious and questioning mindset
• Clear and confident communicator

What success looks like

• Stakeholders trust the data and use it in decision making
• MI is readily available, consistent, and easy to interpret
• Performance issues are identified early and explained clearly
• The organisation has improved visibility over its portfolio and operations

Why join the business

• Opportunity to play a meaningful role in evolving and strengthening the existing data and MI capability within a growing insurance MGA at an important stage of its development
• High impact position where your work directly influences portfolio insight, commercial decisions and discussions with key stakeholders
• Opportunity to take an existing data foundation and bring it to the next level, rather than inheriting heavy legacy complexity.
• Close collaboration with pricing, underwriting, operations and senior leadership, giving strong exposure to how the business operates end to end
• Practical, real world data challenges with clear commercial and regulatory relevance
• Environment that values clear thinking, ownership and high quality delivery
• Strong opportunity to deepen technical, analytical and domain knowledge in insurance data, with scope to grow responsibility and influence as the data capability maturing