Must Have Technical/Functional Skills
Snowflake, Cortex AI, Python and Insurance Domain on AWS Cloud, Talend ETL
Roles & Responsibilities
The Snowflake Lead will serve as the onsite technical lead for CLEARBROOK s enterprise data platform, responsible for end to end Snowflake solution design, development leadership, and AI/advanced analytics enablement. The role requires deep hands on expertise in Snowflake, strong data engineering fundamentals, and the ability to integrate AI/ML driven use cases into the Snowflake ecosystem while coordinating with offshore teams.
Snowflake Production Support
- Perform root cause analysis for job failures and data analysis & fixes
- Perform Month End Closing Activities
Snowflake Development & Architecture
- Lead design and development of Snowflake schemas, tables, views, streams, tasks, and Snowpipes
- Define and enforce best practices for performance optimization (warehouse sizing, clustering, query tuning)
- Own Snowflake security architecture: RBAC, role hierarchy, data masking, row/column level security
- Oversee promotion of code across environments using CI/CD practices
Data Engineering & Integration
- Lead development of batch and near real time ingestion pipelines using Talend / Qlik Replicate / Snowpipe
- Ensure data quality checks, reconciliation, and schema drift handling
- Guide integration from insurance source systems (Policy, Claims, Billing, Reinsurance) into Snowflake
- Provide technical oversight for SQL, Python, and ELT based transformations
AI / Advanced Analytics Enablement
- Enable AI/ML use cases on Snowflake, including:
o Feature engineering datasets for ML models
o Snowpark (Python) based data processing
o Integration with external ML platforms (Databricks / SageMaker / Azure ML where applicable)
- Support AI driven insights such as:
o Claims triage & risk scoring
o Fraud detection inputs
o Premium leakage and pricing analytics
- Guide teams in using Python, SQL, and Snowflake native capabilities for data science workloads
Core Technical Skills
- Snowflake: Advanced SQL, Performance Tuning, Security, Snowpipe, Streams & Tasks
- Data Engineering: ELT/ETL patterns, data modeling, CDC concepts
- Python: Data processing, automation, Snowpark (preferred)
- Strong understanding of cloud data platform architecture (AWS preferred)
AI / Analytics Skills
- Hands on exposure to AI/ML pipelines (feature preparation, training data creation)
- Experience supporting ML models through data engineering and operationalization
- Familiarity with Python ML libraries (scikit learn, pandas, NumPy) applied from a data engineering perspective
- Understanding of model lifecycle support (data refresh, monitoring, retraining inputs)
Domain & Soft Skills
- Insurance domain experience (P&C / Specialty Insurance strongly preferred)
- Strong communication skills for onsite customer interaction
- Ability to translate business requirements into scalable data & AI solutions
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