Snowflake Lead Data Engineering

VOLTO Consulting; United States; Presencial; USD 170 000 - 250 000; Tempo integral

Resumo da oferta

CLEARBROOK is seeking a Snowflake Lead to own end-to-end data platform design and AI enablement in a remote, full-time role. The candidate will guide development, security, and CI/CD practices while coordinating with offshore teams.

You will work on Snowflake schemas, data pipelines with Talend and Python, and integrate AI/ML use cases for insurance-domain workloads in an AWS cloud environment.

Qualificações

• 12–15 years of experience in data engineering / analytics leadership.
• Hands-on expertise with Snowflake, Python and Talend ETL in a cloud environment.
• Experience delivering AI/ML use cases within Snowflake and data platforms.

Responsabilidades

• Lead design and development of Snowflake schemas, tables, views, streams and Snowpipes.
• Define performance best practices and enforce security (RBAC, data masking).
• Oversee CI/CD, code promotion across environments and offshore coordination.
• Develop batch and near real-time ingestion pipelines using Talend and Snowpipe.
• Enable AI/ML use cases on Snowflake and integrate with external platforms.

Conhecimentos

Insurance domain knowledge

Data platform leadership

AI/ML enablement

Ferramentas

Snowflake

Cortex AI

Python

Talend ETL

AWS Cloud

Descrição da oferta de emprego

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