Data Engineer

We’re the UK’s largest mutual life, pensions and investment company, offering protection, long-term savings and asset management products and services.

Job Title: Data Engineer

Contract Type: Permanent

Location: Edinburgh or Glasgow or Alderley Edge

Working style: Hybrid 50% home/office based

We have a fantastic opportunity for a Data Engineer to join Royal London. The successful candidate will be responsible for identifying, defining, managing, and delivering data, tools, and other technical assets to enable analytics, data science, and machine learning projects. These initiatives aim to generate insights, address key business questions, solve business problems, and support decision-making at all levels of the organisation.

In addition to these responsibilities, the Data Engineer will assist junior team members, promoting engineering best practices and maintaining technical standards. The role also involves supporting the delivery of multiple projects across the team, being involved in data, tooling, and technical practices related to data engineering for business intelligence, analytics, data science, and machine learning.

About the role

Source and prepare data for use in Business Intelligence (BI), Analytics, and Data Science projects and initiatives.
Engage with stakeholders and subject matter experts (SMEs) to identify new opportunities to apply these techniques.
Source, evaluate, interpret, and manage multiple disparate data sources.
Design and develop data pipelines for cloud platforms.
Design and develop analytics tools that can be used by the team and by wider business users.
Prototype solutions to explore business hypotheses in an agile and iterative way, supporting a learn fast/fail fast methodology.
Deploy and productionize data pipelines created by the team through CI/CD so that they are available for consumption by the data science and data visualization team.  

About you

An understanding of Business Intelligence and analytics languages and tools, including Python, SQL, Pyspark.
Knowledge of applying data science techniques, including predictive modelling, data mining, and the analysis of large datasets.
Knowledge of data engineering and the application of data management design, such as Data Lakes and Data Warehouses.
Some experience with cloud-based data and analytics technologies, including Azure Data Factory and DataBricks, would be beneficial but not essential
Good knowledge of software engineering and architecture principles, including expert knowledge of the Software Development Life Cycle (SDLC).  

About Royal London

We’re the UK’s largest mutual life, pensions and investment company, offering protection, long-term savings and asset management products and services.   

Our   

Inclusion, diversity and belonging 

We’re an employer. We celebrate and value different backgrounds and cultures across Royal London. Our diverse people and perspectives give us a range of skills which are recognised and respected – whatever their background