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Snowflake Lead Data Engineer

Ztek ConsultingUnited States🇺🇸United StatesPosted 12 Aug 2026

Why This Role Stands Out

This on-site Lead Data Engineer role offers a fantastic opportunity to architect and lead the development of an enterprise data platform, directly impacting AI and advanced analytics enablement within the insurance domain. You'll thrive here if you possess deep Snowflake expertise, strong data engineering fundamentals, and enjoy driving innovative solutions in a collaborative environment. Take this chance to significantly shape data strategy and advance your career!

Quick Overview

Work Type
On Site
Level
Mid Senior

Job Description

Job Role: Snowflake Lead Data Engineer

Location: New York, NY/Remote

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 Snow pipes
  • 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 / Snow pipe
  • 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, Snow Pipe, 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

Skills

SQL
AWS
ETL
NumPy
Snowflake
Azure
Databricks
Pandas
Python
Qlik

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