Requirements:
8+ years of experience in Data Architecture, Data Engineering, or enterprise data platform development.
Solid expertise in Snowflake architecture, data warehousing, and enterprise-scale data platforms.
Hands-on experience with AWS cloud services and designing scalable, cloud-based data solutions.
Solid experience with AWS Glue, Apache Airflow, and dbt for data integration and transformation.
Expertise in data modeling, ETL/ELT architecture, data pipelines, and data integration patterns.
Robust proficiency in SQL and Python for data processing and automation.
Experience designing secure, scalable, and high-performance data architectures.
Experience within the insurance domain is preferred.

Responsibilities:
Design and implement scalable enterprise data architectures using Snowflake and AWS.
Develop architectures for data ingestion, transformation, integration,



and consumption across enterprise systems.
Design and optimize ETL/ELT pipelines using AWS Glue, Apache Airflow, dbt, and related technologies.
Define data models, architecture standards, integration patterns, and technical best practices.
Optimize Snowflake environments for performance, scalability, security, and cost efficiency.
Collaborate with engineering, analytics, and business teams to translate data requirements into effective technical solutions.
Provide technical leadership and guidance to data engineering teams throughout the implementation process.
Ensure data solutions meet enterprise standards for security, governance, reliability, and performance.

📌 Aws Snowflake Architect Markham
🏢 HR POD - Hiring Talent Globally
📍 Markham