Snowflake Lead Data Engineering

Remote

Fulltime - Need only independent VISA Holders

Job Description

12 - 15 years of experience

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

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