Data Engineer (Databricks)

Responsibilities

• ● At M&G, our purpose is to give everyone real confidence to put their money to work. With a heritage dating back more than 175 years, we have a long history of innovation in savings and investments, combining asset management and insurance expertise to offer a wide range of solutions.
• ● Our two distinct operating segments, Asset Management and Life, work together to provide access to balanced, long-term investment and savings solutions.
• ● Through telling it like it is, owning it now and moving it forward together with care and integrity; we are creating an exceptional place to work for exceptional talent.
• ● We will consider flexible working arrangements for any of our roles and offer workplace adjustments to ensure you have the support you need to succeed in your role.
• ● A new solution for the validation and transformation of policyholder data used in actuarial modelling and assumption setting is being built.This role will build and maintain data pipelines to take policyholder data and transform and validate it for use in actuarial models. These data systems need to be robust, reliable, efficient, and meet actuarial modelling and ass
• ● umption setting requirements.
• ● The Data Engineer supports the delivery of high-quality data solutions that underpin actuarial valuation and reporting, and strategic decision-making. Working collaboratively with stakeholders, the role ensures data is structured, governed, and transformed for actuarial use.
• ● Design, build, and maintain scalable data pipelines that validate and transform data to meet actuarial modelling requirements.
• ● Implement checks and controls to ensure actuarial input data is complete, accurate, reconciled and available when required.
• ● Collaborate with stakeholders to understand data needs and translate them into effective technical solutions.
• ● Work with data suppliers to ensure data loads are complete and controlled.
• ● Work with suppliers and actuarial users to resolve data exceptions
• ● Monitor and optimise data performance, resolving issues and improving efficiency where needed.
• ● Contribute to data governance, including documentation, standards, and controls.
• ● Maintain runbooks or support documentation
• ● Works independently on well-defined deliverables and escalates material risks and issues appropriately
• ● Key Knowledge, Skills and Experience:
• ● Strong understanding of data structures, databases, and data modelling concepts.
• ● Ability to manage and process large datasets with attention to accuracy and quality.
• ● Familiarity with data governance and best practices in data management.