Snowflake Data Architect

Infosys; Bengaluru; On-site; INR 4,500,000 - 6,500,000; Full time

Job summary

Infosys is seeking a Senior Data Architect to design end-to-end ceded reinsurance data models and data platforms across lifecycle stages. You will work with actuarial, finance, and analytics stakeholders to ensure accurate views and auditable data lineage.

The role emphasizes strong SQL/Python, cloud data platforms (Snowflake, Databricks, Azure/AWS), and real-time data feeds via Kafka, with a focus on governance and regulatory reporting.

Qualifications

• Experience designing end-to-end ceded reinsurance data models across lifecycle.
• Strong hands-on with treaty types and recoveries in reinsurance domain.

Responsibilities

• Design and implement data architectures for ceded reinsurance across lifecycle, ensuring accuracy and auditable lineage.
• Collaborate with actuarial, finance, and analytics teams, enabling regulatory reporting and BI consumption.
• Drive data quality, governance, and reconciliation for ceded domains.

Skills

Data modeling

SQL

Python

Executive communication

Stakeholder management

Tools

Snowflake

Databricks

Azure

AWS

Fivetran

Apache Kafka

Power BI

Tableau

Job description

• Design end-to-end ceded reinsurance data models across the lifecycle: o Treaty & facultative placements, layers, limits, participations o Premium cessions, commissions, reinstatements o Claims, accruals, recoveries, cash calls, settlements
• Define Gross, Ceded, and Net data views with consistent grain across: o Underwriting year, accident year, accounting and reporting periods
• Architect data structures supporting actuarial triangles (paid, incurred, ultimates) and ultimate recoveries analysis
• Enable accruals, credit control, and recoveries analytics, including counterparty exposure, overdue balances, and leakage tracking
• Drive ceded reinsurance data products for actuarial, finance, management, and regulatory reporting
• Design data models and reporting layers to support QMA and statutory returns, ensuring auditability, lineage, and consistency
• Establish data quality, reconciliation, and governance frameworks for ceded reinsurance domains
• Act as a trusted advisor to Reinsurance, Finance, Actuarial, Claims, and Analytics stakeholders.

• Design end-to-end ceded reinsurance data models across the lifecycle: o Treaty & facultative placements, layers, limits, participations o Premium cessions, commissions, reinstatements o Claims, accruals, recoveries, cash calls, settlements
• Define Gross, Ceded, and Net data views with consistent grain across: o Underwriting year, accident year, accounting and reporting periods
• Architect data structures supporting actuarial triangles (paid, incurred, ultimates) and ultimate recoveries analysis
• Enable accruals, credit control, and recoveries analytics, including counterparty exposure, overdue balances, and leakage tracking
• Drive ceded reinsurance data products for actuarial, finance, management, and regulatory reporting
• Design data models and reporting layers to support QMA and statutory returns, ensuring auditability, lineage, and consistency
• Establish data quality, reconciliation, and governance frameworks for ceded reinsurance domains
• Act as a trusted advisor to Reinsurance, Finance, Actuarial, Claims, and Analytics stakeholders.

Ceded Reinsurance Domain (Mandatory)

• Strong hands-on experience with: o Treaty types (QS, Surplus, XoL, Stop Loss) and Facultative reinsurance o Recoveries, accruals, cash calls, commutations, and credit control o Gross / Ceded / Net actuarial and financial views
• Experience supporting triangles, ultimates, and regulatory (QMA) reporting Data Architecture & Technology
• Expert in conceptual, logical, and physical data modeling
• Strong experience with cloud data platforms (Snowflake, Databricks, Azure/AWS)
• Proven use of: o Fivetran for scalable ingestion of reinsurance, finance, and bordereaux data o Apache Kafka for event-driven and near real-time claims, recoveries, and financial feeds
• Advanced SQL and working knowledge of Python
• Experience supporting analytics and BI consumption (Power BI / Tableau). Personal Attributes
• Strong analytical mindset with attention to financial and contractual detail
• Ability to bridge actuarial, finance, and data engineering teams
• Executive-level communication and stakeholder management skills
• Comfortable operating in complex, global reinsurance environments.