Data Engineer

• Engineer DUAL Personal Lines’ strategic data platforms, especially the Data Lakehouse
• Provide technical expertise in data engineering, analysis, orchestration, and enrichment
• Build data solutions to address changing requirements, new requests, and incidents
• Build, test, and deploy data products while maintaining governance, change control, accountability, data quality, and data security
• Consult business analysts, developers, and system owners to maintain agreed data standards
• Assess the impact of changes on the data model and prevent issues affecting operational, analytical, and reporting environments
• Collaborate with data teams and system owners to maintain the data model and data integrity across the data lakehouse
• Support underwriting analytical teams and reporting analysts with accurate data for underwriting and performance analysis and reporting
• Support delivery of API interfaces, data models, data sharing, RDM/MDM tools, and ML endpoints
• Work within Agile delivery and Dev Ops methodologies to deliver incremental platform changes and data products
• Work with the Group Data Science team to product ionise ML pipelines
• Collaborate with stakeholders across Underwriting, Operations, Finance, Risk & Compliance, and HR
• Facilitate common approaches, standards adherence, and cooperation between DUAL Personal Lines and the DUAL Data Team
• Help drive future data investments, including articulating ROI and assessing benefits realisation

• Strong knowledge of Data Management principles in a Lakehouse architecture
• At least 5 years’ experience in data engineering and building data pipelines
• Proven track record in Data Engineering and supporting the business to gain true insight from data
• Experience in data integration and modelling including ELT pipelines
• Hands-on experience designing and delivering solutions using Azure Data Factory, Azure Databricks, Azure Storage, and Azure Dev Ops
• Strong proficiency in Python and SQL
• Experience working with Data Architects for technical design
• Experience designing data models, including Star Schema, for use in Power BI
• Insurance analysis, MI, or reporting experience
• Understanding and adherence to CI/CD principles
• Ability to work quickly, efficiently, and methodically
• Strong team-player capabilities and confidence in ability
• Very strong communication, influencing, and negotiation skills
• Commercial awareness and knowledge of current industry and technology issues
• Planning, organising, and managing skills, with ability to prioritise
• Good understanding of data operations
• Broad knowledge and understanding of insurance principles, products, and services
• Self-starter with passion and ability for learning new skills and technologies
• Nice to have: experience working alongside Data Science teams to assist with building and deploying Machine Learning models
• Nice to have: experience working with infrastructure-as-code tools for deploying resources

Demonstrates strong expertise in Data Engineering, particularly in Lakehouse architecture, with proficiency in building data pipelines and integrating data solutions. Capable of collaborating across teams to ensure data integrity and governance while delivering insights for underwriting and performance analysis.

• Data Engineering
• Azure Data Factory
• Python
• SQL
• Data Integration

• Data Management Principles
• Building Data Pipelines
• Data Integration
• Data Modelling
• ELT Pipelines
• Designing Data Models
• Star Schema
• Machine Learning
• Infrastructure-as-Code
• CI/CD Principles

• Strong Communication Skills
• Team-Player Capabilities
• Planning and Organising Skills
• Negotiation Skills
• Commercial Awareness

• Insurance Analysis
• Data Governance
• Data Quality
• Data Security
• Data Operations

• Azure Databricks
• Azure Storage
• Azure Dev Ops
• Power BI
• Data Lakehouse