Analytics Engineer

We are seeking a business-minded Analytics Engineer with deep expertise in the Non-Life and Health Insurance domains who will act as the vital bridge between our core business operations and our data infrastructure. Managing insurance data lifecycles will be your primary focus, ranging from policy underwriting, claims reserve changes, and earned vs. unearned premiums.

Functions (Duties and Responsibilities):

• Insurance Data Modeling

- Design and optimize robust, business-centric data models (Star and Snowflake schemas) within SSMS that accurately map the complex data lifecycles of insurance policies and claims.

• ETL Development & Optimization

- Build, scale, and maintain stable ETL pipelines using SSIS and complex T-SQL stored procedures, ensuring clean and optimized structures for business analytics.

• Business Logic Implementation

- Translate nuanced insurance metrics directly into the data layer, including Gross Written Premium (GWP), Net Earned Premium, Loss Ratios, Claims Reserves etc.

• Historical Reporting & Truth

- Solve complex insurance data problems, such as retroactively adjusted claims, policy endorsements, and historical point-in-time (as-of) financial reporting using advanced T-SQL.

• Stakeholder Collaboration

- Partner closely with Actuaries, Underwriters, Claims Managers, and Finance teams to turn messy production source data into reliable, intuitive analytical data products.

Job Skills And Qualifications:

· Education: BS in Computer Science, Data Analytics, Actuarial Science, Finance or related quantitative field

· Domain Expertise: Minimum 3 to 5 years of Insurance data experience or related field

· Business Acumen: Strong understanding of core insurance financials, policy lifecycles, and claims states.

· Technical Expertise: Advance proficiency in SSMS, SSIS, TSQL, TSQLT. Cloud is a plus.

· Analytical Mindset: Proven ability to prioritize business context and data quality over pure engineering output.

**Candidates who can start immediately are preferred.