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Metro location, generalist data-engineer title, and mid-level experience range drive medium competition.
Strong actuarial, financial-services and audit requirements reduce cross-industry transferability, so sensitivity is high.
Explicit 4–10 years plus FS audit controls and required SQL/Databricks/Spark skills make shortlisting strict (high).
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Operate, maintain, and update data pipelines validating, transforming, and enriching policyholder data for actuarial modelling and assumption setting.
Ensure accuracy, completeness, and control of actuarial input data through checks, controls, and collaboration with data suppliers.
Produce and maintain documentation, resolve data issues, support stakeholders, and deliver data products with agreed standards and timelines.
4-10 years of relevant Data Engineering experience.
Experience in Financial Services or a closely related heavily audited environment with operating controls and audit evidence production.
Strong skills in SQL, data management, data modelling, and advanced Excel (formulas, pivot tables, Power Query).
Bachelor’s or Master’s degree; Data Engineering certifications advantageous but not mandatory.
Experienced in building and maintaining scalable data pipelines focused on data validation and transformation for actuarial or financial use cases.
Comfortable working independently within established processes while managing workload and escalating risks when necessary.
Able to communicate clearly with both technical and non-technical stakeholders, supporting data governance and continuous process improvement.