YochanaVerified Job Source

Data Architect: Snowflake

Markham, ON
On-site
Posted Oct 1, 2026
1 position

Opens an external site

Employment type: Full-time
Experience level: Senior · 5+ years
Apply by: Oct 29, 2026
Posting language: English
Working hours: 40 hours per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

Architect and implement scalable, secure, high-performance Snowflake data solutions on AWS, including migration of existing data warehouse workloads to Snowflake. Collaborate with cross-functional teams to deliver governed data pipelines, models, and products while evaluating technologies and documenting architecture and data flows.

Job details

Position Name – Data Architect: Snowflake Type of hiring – Fulltime Location – Markham, ON (Mandatorily need to visit office 3 days – Mon/Tue/Wed) Job Description: Role Purpose: The purpose of the Data Architect: Snowflake role is to: Architect and implement advanced data solutions using Snowflake on AWS, ensuring scalable, secure, and high-performance data environments. Migration of the existing Datawarehouse solution to Snowflake Technology platform evaluations in the data and analytics space Collaborate with cross-functional teams (data engineers, AI engineers, business, solution architects) to translate business requirements into technical solutions aligned with data strategy. Ensure data governance, security, and compliance within the Snowflake ecosystem, adhering to regulatory and organizational standards. Experience and Capabilities Extensive experience (8+ Years) in data architecture and engineering, with a proven track record in large-scale data transformation programs, ideally in insurance or financial services. Proven experience in architecting and implementing advanced data solutions using Snowflake on AWS Expertise in design and orchestrating data acquisition pipelines using AWS Glue for ETL/ELT, Snowflake OpenFlow and Apache Airflow for workflow automation, enabling seamless ingestion of different data from diverse sources. Proven experience in DBT to manage and automate complex data transformations within Snowflake, ensuring modular, testable, and version-controlled transformation logic. Experience in implementing the lake house solution, Medallion architecture for financial or insurance carriers Experience in optimizing and tune Snowflake environments for performance, cost, and scalability, including query optimization and resource management, Experience in architecting/lead migration of workloads from Cloudera to Snowflake Design Streamlit apps and define new capabilities and data products leveraging snowflake ML and LLOPS capabilities. Experience in evaluating the data technology platform including data governance suites, data security products Exposure to enterprise Datawarehouse solution like Cloudera, AWS Redshift and informatica tool sets- IDMC, PowerCenter, BDM Develop robust data models and data pipelines to support data transformation, integrating multiple data sources and ensuring data quality and integrity. Document architecture, data flows, and transformation logic to ensure transparency, maintainability, and knowledge sharing across teams. Strong knowledge of data lifecycle mgmt., data retention, data modelling and working knowledge of cloud computing, and modern development practices. Experience with data governance, metadata management, and data quality frameworks (e.g., Collibra, Informatica). Experience in converting policy/data conversion from legacy to modern platform Deep expertise in Snowflake (SnowPro Advanced Certification preferred), with hands-on experience delivering Snowflake as an enterprise capability. Hands-on experience with AWS Glue for ETL/ELT, Apache Airflow for orchestration, and dbt for transformation (preferably deployed on AWS ECS). Proficiency in SQL, data modeling, ETL/ELT processes, and scripting languages (Python/Java). Familiarity with data mesh principles, data product delivery, and modern data warehousing paradigms.

What you’ll do

Requirements

Requires 8+ years of data architecture and engineering experience, ideally in large-scale transformation programs within insurance or financial services, and deep hands-on expertise with Snowflake on AWS. Candidates should have experience with AWS Glue, Airflow, dbt, data governance and quality, data modeling, and workload migration; SnowPro Advanced certification is preferred.