Senior Manager - Data Engineer- Methodology & Assumption (M&A) Actuarial Policyholder Data Team
On-siteMumbai, Maharashtra, India
Job Summary
Design and maintain scalable data pipelines that validate, transform, and enrich policyholder data for actuarial modelling and assumption setting. Implement checks and controls to ensure input data is complete, accurate, and reconciled, while collaborating with suppliers to manage data loads and resolve exceptions. Monitor data performance, optimize efficiency, and proactively investigate issues raised by stakeholders or found during pre-emptive analysis. Maintain runbooks, process documentation, and data dictionaries to support auditability and operational resilience within the Methodology & Assumption team. Work independently on Model Points Data Production and Experience Analysis tasks, escalating material risks appropriately.
Required Qualifications
- Strong understanding of data structures, databases, and data modelling concepts
- Experience working on data pipelines with data transformation, validation and storage processes
- Ability to manage and process large datasets with attention to accuracy and quality
- Familiarity with data governance and best practices in data management
- Strong problem-solving skills and the ability to work collaboratively across teams
- Experience working in Financial Services or a similar heavily audited environment with an understanding of operating controls and producing audit evidence
- Clear communication with both technical and non-technical stakeholders
- Proactive approach to identifying and resolving issues
- Commitment to continuous improvement and delivering high-quality outcomes
- SQL Data management and modelling
- Experience maintaining documentation, controls, and governance evidence to support auditability and operational resilience
- Experience using Excel, Power BI, and/or Python to analyse data, automate checks, and produce reports or dashboards
- Advanced Excel skills, including formulas, pivot tables, lookups, data validation, Power Query, and reconciliation techniques
- 4-10 years of relevant Data Engineering experience
- Financial services experience, or a closely related field
- Bachelor's Degree / Master's Degree
Desired Qualifications
- Any Data Engineering Certifications
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