Data Engineer

Key member of the team, engineering DUAL Personal Lines' strategic data platforms, chief of which is the Data Lakehouse, to enable the continuous enhancement of DUAL Personal Lines' underwriting analytical capabilities.

Provide technical expertise in data engineering, analysis, orchestrations, and enrichment.

Build data solutions where required to address changing requirements - managing new requests and incidents.

Building, testing and deployment of data products while remaining true to governance principles including change control, accountability, data quality, and data security.

Consult the DUAL Group data team's business analysts, developers and system owners to avoid divergence from agreed data standards.

Assesses the impact of change on DUAL Personal Lines' data model to determine and avoid any potential issues which may hinder our operational, analytical and reporting environments.

Actively collaborates with data teams and system owners to maintain the data model and data integrity throughout the DUAL Group data lakehouse.

Closely support underwriting analytical teams and reporting analysts to ensure data is accurately represented for use in underwriting and performance analysis and reporting.

Build knowledge and expertise of DUAL Personal Lines' systems with other data team members.

Working with other members of the data team and wider business to support delivery of additional project components (API interfaces, Data Models, Data Sharing, RDM/MDM tools, ML Endpoints).

Working within an Agile delivery / DevOps methodology to incremental change to the overall data platform to deliver additional data products to provide value to stakeholders.

Working with the Group Data Science team to productionise ML pipelines into the overall data platform solution.

Work collaboratively with internal stakeholders across DUAL Personal Lines including but not limited to Underwriting teams, Operations, Finance, Risk & Compliance and HR.

Act as a conduit between DUAL Personal Lines and Dual Data Team to facilitate the sharing of common approaches, adherence to standards, and advocating on behalf DUAL.

Help drive success of future investments in Data within DUAL Personal Lines, including clear articulation of return on investment (ROI) and ongoing assessment of realisation attainment.

Key requirements

• 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 services including Azure Data Factory, Azure Databricks, Azure Storage, Azure DevOps.


• Strong proficiency in Python and SQL


• Experience working with Data Architects for technical design


• Experience on the design of data models (Star Schema) for use in Power BI. Insurance analysis, MI or reporting experience


• Understanding and adherence to CI/CD principles


• 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


• Ability to work quickly, efficiently and methodically.


• A strong team player who is confident in their ability.


• Very strong communication, influencing and negotiation skills. Actively listens to the views of colleagues, but also has the strength of character to challenge where required.


• Has a commercial awareness and stays up to date with current issues affecting the industry and its technologies.


• Proactively sharing best practice with others across the organisation.


• Planning, organising, and managing skills, and ability to prioritise.


• Good understanding of data operations.


• Broad knowledge and understanding of insurance principles, products and services.


• Self-starter, with a passion and ability for learning new skills and technologies