Senior Data Analyst

Responsibilities

• Work closely with business stakeholders (Underwriting, Claims, Actuarial, Finance, Operations) to understand reporting and analytics needs.
• Translate business questions and KPIs into data analysis, reports, and dashboards.
• Conduct requirement‑gathering sessions and prepare business requirement documents (BRDs) and reporting specifications.
• Present insights, trends, and recommendations to business and leadership stakeholders in a clear and concise manner.
• Data Analysis & Reporting:
  Analyze data related to policy lifecycle, claims, premiums, losses, exposure, reserves, and billing.
• Develop and maintain dashboards, reports, and scorecards using BI tools (Power BI, Tableau, etc.).
• Perform trend analysis, variance analysis, and root‑cause analysis.
• Support regulatory, operational, and management reporting.
• Validate data accuracy and ensure consistency across reports.
• Data
  
  Collaboration:
  
  Write and optimize SQL queries to extract and analyze data from enterprise systems.
• Collaborate with data engineering teams on data availability, data quality, and transformations.
• Assist with data reconciliation, data quality checks, and issue resolution.
• Document data definitions, business rules, assumptions, and metrics.

• Insurance Domain Experience (Mandatory):
  Strong hands‑on experience in Insurance (P&C, Life, Annuity, or Reinsurance).
• Solid understanding of:
  Policy lifecycle (Quote, Bind, Issue, Endorse, Renew);
  Claims lifecycle and claims financials;
  Premiums, losses, reserves, exposure;
  Billing and invoicing.
• Experience working with insurance platforms such as Guidewire, Duck Creek, Sapiens, or similar is highly preferred.
• Technical & Analytical
  
  Skills:
  
  Strong experience as a Data Analyst in enterprise environments.
• Proficiency in SQL for querying and data analysis.
• Hands‑on experience with BI tools:
  Power BI (preferred);
  Tableau / Qlik (or similar).
• Strong experience with Excel (pivot tables, formulas, data analysis).
• Experience working with relational databases (SQL Server, Oracle, PostgreSQL).
• Familiarity with data warehousing and dimensional models.

• Exposure to Azure / Cloud data platforms.
• Experience with Power BI semantic models, DAX, and Power Query.
• Knowledge of data governance, metadata, and data quality frameworks.
• Experience working in Agile/Scrum delivery models.
• Ability to support executive dashboards and self‑service BI.