Snowflake Lead Data Engineering

Job description

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:
• Feature engineering datasets for ML models
• Snowpark (Python)–based data processing
• Integration with external ML platforms (Databricks / SageMaker / Azure ML where applicable)
• Support AI driven insights such as:
• Claims triage & risk scoring
• Fraud detection inputs
• Premium leakage and pricing analytics
• Guide teams in using Python, SQL, and Snowflake native capabilities for data science workloads

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 Salary Range: $110,000 to $130,000 per year </div

Qualifications

BACHELOR OF COMPUTER SCIENCE