Role Summary
As a Senior MI Analyst Developer, you will play a pivotal role in designing, developing, and optimising the reporting and analytics layer that supports underwriting, actuarial, risk, finance, and regulatory functions across the reinsurance business. You will own the end‑to‑end lifecycle of MI solutions, from data modelling and semantic layer design to dashboard development, performance optimisation, and stakeholder engagement. This is a hands on role with hybrid working where the expectation is to work 3 days in the office.
Role Accountabilities & Requirements
- Designing and developing enterprise‑grade Power BI solutions, including data models, DAX measures, and interactive dashboards.
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Building robust star schemas and dimensional models aligned to Kimball and/or Inmon methodologies.
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Creating and maintaining semantic models (Power BI datasets, Analysis Services models, or Fabric semantic layer) to support self‑service analytics.
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Working closely with Data Engineering to define clean, well‑structured data layers optimised for reporting.
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Translating complex business requirements into logical and physical data models.
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Implementing data quality checks, validation rules, and reconciliation logic within the reporting layer.
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Optimising Power BI performance through query folding, aggregation tables, incremental refresh, and DAX optimisation.
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Developing automated reporting frameworks for regulatory, operational, and financial MI.
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Collaborating with actuarial, underwriting, exposure management, and finance teams to ensure MI outputs are accurate, timely, and aligned to business needs.
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Managing Power BI workspace governance, dataset refresh schedules, RLS/OLS security, perspectives, calculation groups and deployment pipelines.
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Producing clear documentation, data dictionaries, and user guides to support adoption and self‑service analytics.
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Providing mentorship to analysts and contributing to the evolution of MI standards, best practices, and reporting frameworks.
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Designing and developing enterprise‑grade Power BI solutions, including data models, DAX measures, and interactive dashboards.
-
Building robust star schemas and dimensional models aligned to Kimball and/or Inmon methodologies.
-
Creating and maintaining semantic models (Power BI datasets, Analysis Services models, or Fabric semantic layer) to support self‑service analytics.
-
Working closely with Data Engineering to define clean, well‑structured data layers optimised for reporting.
-
Translating complex business requirements into logical and physical data models.
-
Implementing data quality checks, validation rules, and reconciliation logic within the reporting layer.
-
Optimising Power BI performance through query folding, aggregation tables, incremental refresh, and DAX optimisation.
-
Developing automated reporting frameworks for regulatory, operational, and financial MI.
-
Collaborating with actuarial, underwriting, exposure management, and finance teams to ensure MI outputs are accurate, timely, and aligned to business needs.
-
Managing Power BI workspace governance, dataset refresh schedules, RLS/OLS security, perspectives, calculation groups and deployment pipelines.
-
Producing clear documentation, data dictionaries, and user guides to support adoption and self‑service analytics.
-
Providing mentorship to analysts and contributing to the evolution of MI standards, best practices, and reporting frameworks.
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Any additional duties, as assigned.
Essential Skills and Abilities
- 5–7+ years of experience in MI, BI development, analytics engineering, or data modelling.
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Expert‑level skills in Power BI, including DAX, Power Query (M), data modelling, and performance tuning.
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Strong experience designing star schemas, snowflake schemas, and dimensional models using Kimball principles.
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Understanding of Inmon‑style enterprise data warehousing and how it integrates with downstream reporting layers.
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Strong SQL skills, including complex joins, window functions, and optimisation techniques.
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Experience working with Azure data sources (Synapse, Databricks, SQL DB, Data Lake, Fabric).
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Ability to translate business requirements into clear, scalable MI solutions.
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Strong understanding of data governance, lineage, and metadata management.
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Experience building semantic models for enterprise reporting.
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Excellent communication skills and the ability to work with senior stakeholders across actuarial, underwriting, risk, and finance.
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Line management experience.
Desirable Skills and Abilities
- Experience working with reinsurance or insurance data domains, including exposure, claims, treaties, and catastrophe modelling.
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Familiarity with Azure environment and/or Fabric (Data Engineering, Warehouse, Lakehouse, Semantic Models).
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Experience with Azure Analysis Services or Power BI Premium.
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Knowledge of regulatory reporting (Solvency II, IFRS 17, Consumer Duty).
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Understanding of data quality frameworks and reconciliation processes.
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Exposure to Python for light data preparation or automation.
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Power BI or Azure certifications (e.g., PL‑300, DP‑500).
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Experience mentoring analysts or contributing to MI/BI capability uplift.
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Ability to contribute and define to enterprise‑wide reporting standards and semantic modelling conventions.
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Experience implementing Power BI deployment pipelines and DevOps‑aligned release processes.
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Strong understanding of data product design and domain‑driven analytics.
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Experience with large‑scale dataset governance, Premium capacity management, and RLS/OLS strategy.
Management Duties
- Yes, there will be a transition to management duties.
