Requirements:

- 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.
- Robust 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:

- 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