Data Analyst

7-9 years of experience as a Data Analyst, with at least 5 years supporting Finance within the insurance industry.

Hands-on experience with Vertica/Teradata for querying, performance optimization, and large-scale data analysis.

Advanced SQL skills: proficiency in Python is a strong plus.

Proven ability to write detailed source-to-target mapping documents and collaborate with technical teams on data integration.

Experience working in hybrid onshore-offshore team environments.

Knowledge of data engineering principles: ETL/ELT, data lakes, and data warehousing.

Deep understanding of data modeling concepts and experience working with relational and dimensional models.

Strong communication skills with the ability to clearly explain technical concepts to non-technical audiences.

A strong understanding of statistical concepts, probability and accounting standards, financial statements (balance sheet, income statement, cash flow statement), and financial ratios.

Strong understanding of life insurance products and business processes across the policy lifecycle.

Investment Principles: Knowledge of different asset classes, investment strategies, and financial markets.

Quantitative Finance: Understanding of financial modeling, risk management, and derivatives.

• Regulatory Framework: Awareness of relevant financial regulations and compliance requirements.
• The Ideal Qualifications
• Technical Skills:

Proven track record of Analytical and Problem-Solving skills.

A solid understanding of Financial Accounting Systems and knowledge of accounting principles, reporting and budgeting

Strong data analysis skills for extracting insights from financial data

Proficiency in data visualization tools and reporting software is also important.

Experience integrating financial systems with actuarial, policy administration, and claims platforms.

Familiarity with actuarial processes, reinsurance, or regulatory reporting requirements.

Experience with