Technical Data Analyst
Technical Data Analyst joining Gallagher's Data Technology team to analyse complex insurance data, build logical/physical data models, develop dbt transformation pipelines and trusted Snowflake datasets for reporting, analytics and regulatory needs. Hybrid role, 3 days a week in London.
- Compensation
- Not disclosed
- Location
- London
- Work setup
- Hybrid
- Seniority
- Senior
- Employment
- Full time
- Experience
- Not specified
- Category
- Data analytics
- Posted
Skills
Must have
- Previous experience in Insurance, Lloyd's Market, Specialty Insurance or Reinsurance environments
- Source-to-target mapping experience and advanced SQL writing ability
- Ability to reconcile data between source and target datasets using SQL and/or Excel
- Problem-solving ability to trace data discrepancies back to source to identify root cause
- Ability to trace data flows through data structures using ETL toolsets including SQL, SSIS, PowerBI, Snowflake, dbt to define data lineage
- Knowledge of data warehouse principles: dimensional modelling, Kimball, star schemas, incremental loading, master data management
- Understanding and ability to profile data and identify data quality issues
- Requirements gathering and analysis skills
- Hands-on experience with SQL, Snowflake and dbt
Nice to have
- Previous experience and understanding of Policy / Claims data elements
- Around two years of experience as a data professional (non-senior role)
Full description
Introduction
Welcome to Gallagher - a global community of people who bring bold ideas, deep expertise, and a shared commitment to doing what’s right. We help clients navigate complexity with confidence by empowering businesses, communities, and individuals to thrive. At Gallagher, you’ll find more than a job; you’ll find a culture built on trust, driven by collaboration, and sustained by the belief that we’re better together. Whether you join us in a client-facing role or as part of our brokerage division, our benefits and HR consulting division, or our corporate team, you’ll have the opportunity to grow your career, make an impact, and be part of something bigger. Experience a workplace where you’re encouraged to be yourself, supported to succeed, and inspired to keep learning. That’s what it means to live The Gallagher Way.
Overview
We're looking for an experienced Technical Data Analyst to join our Data Technology team. This is an exciting opportunity to help shape and deliver high-quality data products that support reporting, analytics, regulatory requirements and business decision-making across our organisation.
Working at the intersection of business and technology, you'll partner with Data Engineers, Architects, Product Owners and key stakeholders to analyse complex insurance data, develop robust data models and ensure trusted datasets are delivered across our modern cloud data platform.
This role is ideal for someone who combines technical expertise with a genuine interest in solving business problems through data. You'll be comfortable working hands-on with SQL, Snowflake and dbt, while translating business requirements into scalable technical solutions.
This role is not a senior position and would suit so would suit a data professional who has two-years experience and is looking to take the next step in their career. We other hybrid working and the expectations is to be in London 3 days a week.
How you'll make an impactData Analysis & Modelling
- Analyse complex insurance datasets across policy, claims, underwriting, finance and regulatory domains.
- Develop logical and physical data models to support reporting, analytics and operational processes.
- Define, document and maintain business and technical data definitions.
- Conduct data investigations and root-cause analysis to identify issues and support remediation.
- Perform source-to-target mapping and validate transformation logic across multiple systems.
Data Platform Development
- Develop and maintain data transformation pipelines using dbt.
- Build, test and optimise scalable data models within Snowflake.
- Create reusable datasets, metrics and semantic layers that support enterprise-wide analytics.
- Collaborate with Data Engineers to improve data platform performance, reliability and scalability.