AWS Snowflake Solutions Architect

N2P Systems is seeking an experienced AWS Snowflake Solutions Architect to join our enterprise technology delivery team in Toronto, Ontario, Canada. At N2P Systems, you will put 10+ years of hands-on experience with AWS, AWS Data Services and Snowflake to work on mission-critical enterprise systems. This is an existing full-time, hybrid vacancy with N2P Systems.

N2P Systems is seeking an experienced Data & Analytics Solutions Architect to lead the design and modernization of enterprise data, analytics, and AI platforms using AWS and Snowflake. This senior architecture position requires extensive expertise in cloud data engineering, enterprise solution architecture, and modern Lakehouse technologies.

The successful candidate will define end-to-end technical architectures, establish governance and security standards, and guide the delivery of scalable, secure, and high-performance data platforms. The role also involves architecture leadership, technical consulting, stakeholder engagement, and supporting enterprise cloud transformation initiatives, particularly within the BFSI sector.

N2P Systems uses AI to help screen and assess applications for this role. N2P Systems is an enterprise technology consulting and digital solutions firm operating across Canada, the United States and India.

Key Responsibilities:

• Collaborate with business and technology stakeholders to understand enterprise data, analytics, AI, and cloud transformation requirements.
• Define end-to-end architectures for AWS and Snowflake-based enterprise data, analytics, and AI platforms.
• Design scalable, secure, and high-performance Lakehouse solutions using AWS Data Services, Snowflake, Apache Iceberg, Snowflake Open Catalog, and Snowflake Horizon Catalog.
• Architect enterprise data ingestion, integration, batch processing, streaming, and data engineering solutions.
• Design AI-enabled analytics capabilities using Snowflake Cortex, semantic models, and governed data access frameworks.
• Establish platform-wide standards for data governance, security, metadata, lineage, observability, and responsible AI.
• Lead data platform modernization, migration, and cloud transformation initiatives on AWS.
• Define architecture standards, reusable frameworks, engineering best practices, and DataOps delivery models.
• Provide technical direction across solution design, implementation, testing, migration, deployment, and production support.
• Conduct architecture reviews, identify technical risks and dependencies, and guide teams on mitigation strategies.
• Improve platform performance, operational reliability, and infrastructure cost efficiency across AWS and Snowflake environments.
• Collaborate with data engineers, AI specialists, architects, platform teams, and client stakeholders to deliver enterprise-scale solutions.
• Support solution development, RFP responses, effort estimation, technical presentations, and client workshops.
• Mentor architects and engineers while contributing to technical assessments, capability development, and knowledge-sharing initiatives.
• Develop reusable accelerators, reference architectures, implementation frameworks, and best practices for AWS, Snowflake, and AI solutions.

Required Skills & Qualifications:

• At least 14 years of experience across enterprise data architecture, AWS data platforms, Snowflake, data engineering, and cloud modernization.
• Proven experience designing enterprise solutions using AWS, Snowflake, Cortex, and related technologies across the complete Data-to-Insights lifecycle.
• Strong hands-on expertise in AWS Data Services, Snowflake, Snowflake Cortex, Snowflake Horizon Catalog, Apache Iceberg or Snowflake Open Catalog, Python, PySpark, and SQL.
• Demonstrated experience designing and implementing Lakehouse architectures, enterprise data platforms, and modern analytics solutions on AWS.
• Strong understanding of Snowflake Data Cloud capabilities, including data workflows, ingestion, model management, serverless computing, and performance optimization.
• Expertise in data engineering, including ETL/ELT, batch and streaming integration, APIs, orchestration, data quality, metadata management, lineage, observability, and DataOps.
• Strong understanding of enterprise data architecture principles, including data models, data products, Lakehouse and warehouse patterns, semantic layers, and master/reference data management.
• Experience implementing security, governance, and compliance controls covering IAM/RBAC, encryption, privacy, masking, auditability, and retention.
• Proven ability to lead architecture definition, HLD/LLD preparation, non-functional requirements assessment, migration planning, technical governance, and production readiness.
• Experience supporting cloud transformation, solution development, RFP responses, effort estimation, and client-facing architecture discussions.
• Good understanding of BFSI regulatory, security, privacy, resilience, and audit requirements.
• Bachelor's degree in Computer Science, Engineering, Information Systems, Data Management, or a related discipline.

Preferred Qualifications:

• Experience with Snowflake SQL, Snowpipe, Snowflake Workflows, and Snowflake Model Registry.
• Familiarity with Snowflake Serverless Compute and advanced platform performance optimization.
• Experience developing AI-enabled analytics solutions using Snowflake Cortex, semantic models, and natural language analytics.
• Exposure to responsible AI practices and enterprise AI implementation.
• Professional certifications in AWS Solutions Architecture, Snowflake, Data Engineering, Enterprise Architecture, Security, or AI/ML.

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