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Metro-based mid-level data engineering role at a recognized financial firm with broad skill and experience requirements.
Requires financial services/audit experience and actuarial data familiarity, limiting transferability across industries.
Explicit 4–10 years, required data engineering skills, and audited financial controls make screening fairly strict.
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Operate, maintain, and update data pipelines that validate, transform, and enrich policyholder data for actuarial modelling and assumption setting.
Ensure actuarial input data is complete, accurate, reconciled, and available on time by implementing checks, controls, and monitoring data loads from suppliers.
Own Model Points Data Production and Experience Analysis tasks, delivering outputs with accuracy, consistency and within agreed timelines.
4-10 years of relevant Data Engineering experience in Financial Services or closely related field.
Strong knowledge of data structures, databases, data modeling, and experience with data transformation, validation, and storage processes.
Proficiency in SQL and advanced Excel (formulas, pivot tables, Power Query), with experience in data management, documentation, controls, and audit evidence production.
Bachelor's or Master's degree; Data Engineering certifications are advantageous.
Experienced in building and maintaining scalable data pipelines with focus on accuracy, completeness, and reconciliation of data in a heavily audited financial services environment.
Capable of working independently on well-defined deliverables while collaborating effectively with technical and non-technical stakeholders, including suppliers and actuarial users.
Skilled in data governance, process documentation, issue resolution, and continuous improvement within defined frameworks.