Data Engineer (Analytical Engineering)

Hours Per Week: 35

Contract Type: Full Time

Contract Type: Permanent

Location: Alderley Park (Wilmslow) or Glasgow

Working Style: Hybrid 50% home/office based

We have a fantastic opportunity for an experienced Data Engineer to join Royal London's Analytics Engineering Team within our Group Data & AI Office function. As a Data Engineer you will define, manage, and deliver the data, tools, and other technical assets to enable analytics, data science, and machine learning projects. These initiatives will create insights, answer key business questions, solve business problems, and support decision making at all levels of the organisation. Supporting the Senior Data Engineers in their role as technical lead for the team, helping to set and maintain technical standards. We value great communication skills, as you'll be interacting with internal business areas as an SME for data, tooling and the technical practice around data engineering, analytics, data science and machine learning.

The purpose of the Analytics Engineering team is to create business value through delivery of specific Analytics, Data Science, Machine Learning and Artificial Intelligence projects and initiatives. These initiatives will create insights, answer key business questions, solve business problems, and support decision making at all levels of the organisation. This team supports the other teams within the Analytics & Insight function, providing them with a Data and Analytics service to support their insight activities. The team will also act as a Centre-of-Excellence in Analytics and Data Science, helping to take forward the Group's capability in these areas and our ambition to become "Data Led".

This role is suited to an experienced Data Engineer who has worked on large enterprise data programmes, with advanced experience of Databricks and data analytics.

More about the role:

• Source and prepare data for use in Business Intelligence (BI), Analytics, Data Science and Generative AI projects and initiatives.
• Source, evaluate, interpret, model, and manage multiple disparate data sources.
• Understand, own, and manage the team's data - working with business, technology, and external partners.
• Design, develop and manage the deployment of data pipelines in our cloud platforms (Databricks, primarily), and help the manage heritage on-premises (SQL Server primarily) pipelines and the migration of these.
• Prototype solutions to explore business hypothesis in an agile and iterative way which supports a learn fast/fail fast methodology.
• Productionise data pipelines created by the team through CI/CD so that they are available for consumption for the business, data science, and data visualisation teams, respectively.
• Maintain knowledge of data engineering and machine learning engineering practices including keeping abreast of new developments and changes in the field.
• Maintain knowledge of data-related technologies and practices.
• Help to ensure that robust software engineering practices are adhered to by the team.

More about you:

• Advanced experience of cloud-based Data and Analytics platforms and technologies, Databricks knowledge is essential and some exposure to experience of Fabric and/or Snowflake would be advantageous.
• Advanced experience in data engineering and application of data management design patterns.
• Ideally will have experience in creating Genie Agents, configuring data assets for Natural Language Querying and using Metric Views to create semantic layers.
• Experience of programming languages: SQL, python & pySpark etc.
• Experience of development practices: the use of versioning tools such as GitHub, work tracking tools such as Azure DevOps, or equivalents.
• A proven track record in working in cross-functional projects to a successful conclusion.
• Experience of managing stakeholders.
• A broad understanding of BI and analytics tools, such as PowerBI, Tableau & R.
• Some understanding of Microsoft SQL Server technologies, such as T-SQL and SSIS, would be useful.
• Knowledge of the technology side of Analytics and Data Science, including principles of software engineering.

If you think you would be a great fit for our team at Royal London but don't meet all the requirements of the role, please get in touch as your application will still be considered.

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 People Promise to our colleagues is that we will all work somewhere inclusive, responsible, enjoyable and fulfilling. This is underpinned by our Spirit of Royal London values; Empowered, Trustworthy, Collaborate, Achieve.

We've always been proud to reward employees by offering great workplace benefits such as 28 days annual leave in addition to bank holidays, an up to 14% employer matching pension scheme and private medical insurance.

Inclusion, diversity and belonging

We're an inclusive 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