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AWS Snowflake Architect (Hybrid, Markham, Ontario)

Canada·Markhammid

ArchitectConstruction & Real Estate

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Quick Summary

Key Responsibilities

Design and implement scalable enterprise data architectures using Snowflake and AWS. Develop architectures for data ingestion, transformation, integration, and consumption across enterprise systems.

Requirements Summary

8+ years of experience in Data Architecture, Data Engineering, or enterprise data platform development. Strong expertise in Snowflake architecture, data warehousing,

Technical Tools

ArchitectConstruction & Real Estate

Requirements

~1 min read

8+ years of experience in Data Architecture, Data Engineering, or enterprise data platform development.
Strong 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.
Strong 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.
Strong 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

~1 min read

→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.