Technical Data Analyst
Role Overview
Join Gallagher's Data Technology team to deliver data products supporting reporting, analytics, regulatory requirements, and business decisions.
Work with Data Engineers, Architects, Product Owners, and stakeholders on insurance data and a modern cloud data platform.
The posting says this is not a senior position and would suit someone looking for their next step.
Key Skills for This Role
Full Job Posting
Role overview
Join Gallagher's Data Technology team to deliver data products supporting reporting, analytics, regulatory requirements, and business decisions.
Work with Data Engineers, Architects, Product Owners, and stakeholders on insurance data and a modern cloud data platform.
The posting says this is not a senior position and would suit someone looking for their next step.
Data analysis and modelling
- Analyse policy, claims, underwriting, finance, and regulatory datasets.
- Develop logical and physical data models for reporting, analytics, and operational processes.
- Maintain business and technical data definitions; investigate root causes and support remediation.
- Map data from source to target and validate transformation logic across systems.
Data platform development
- Develop and maintain dbt transformation pipelines and build, test, and optimise Snowflake data models.
- Create reusable datasets, metrics, and semantic layers for enterprise-wide analytics.
- Work with Data Engineers to improve platform performance, reliability, and scalability.
Data quality and technical delivery
- Design data quality checks, reconciliations, and validation controls; investigate and resolve data quality issues.
- Support data governance, standards, and metadata management practices.
- Translate business requirements into data solutions and contribute to data products and analytical services.
Essential experience and skills
- Experience in Insurance, the Lloyd's Market, Specialty Insurance, or Reinsurance.
- SQL skills and hands-on Snowflake experience; proven dbt data transformation and modelling experience.
- Understanding of dimensional modelling, data warehousing, ETL/ELT, and modern cloud data architectures.
- Knowledge of data lineage, metadata management, and data quality frameworks.
- Experience with Git and CI/CD, plus analytical, problem-solving, and stakeholder engagement skills.
Desirable skills
- Python or PySpark, Databricks, Azure Data Factory, Power BI semantic modelling, and data testing or quality assurance frameworks are desirable.
- Experience with a Data Mesh or Data Product operating model is desirable.
Workplace
- Hybrid working is offered, with an expectation to be in London three days a week.
Compensation and benefits
- Competitive compensation, comprehensive benefits, career development and learning, and a collaborative culture are mentioned; no salary amount or cadence is provided.
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