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N2P Systems

AWS Snowflake Solutions Architect

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Nov 29, 2026
Posting language: English
Posted: Oct 30, 2026

Original job description

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.

Apply directly at: https://www.n2psystems.com/jobs/REQ-43712

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More about this job

Responsibilities

Define and lead end-to-end AWS and Snowflake architectures for enterprise data, analytics, and AI platforms, including Lakehouse design, modernization, migration, governance, and security. Guide delivery teams and stakeholders through architecture reviews, implementation, production readiness, performance and cost optimization, client engagements, and technical mentoring.

Requirements

Requires at least 14 years of experience in enterprise data architecture, AWS data platforms, Snowflake, data engineering, and cloud modernization, with hands-on expertise in AWS Data Services, Snowflake, Cortex, Iceberg or Open Catalog, Python, PySpark, and SQL. Candidates should have experience with Lakehouse solutions, governance and security controls, architecture leadership, cloud transformation, and BFSI requirements, plus a bachelor's degree in a related discipline.

Skills

AWS
Snowflake
Snowflake Cortex
Snowflake Horizon Catalog
Apache Iceberg
Snowflake Open Catalog
Lakehouse Architecture
Data Engineering
Python
PySpark
SQL
Data Governance
Data Security
DataOps
Enterprise Architecture
AI-Enabled Analytics

Visa sponsorship

Not detected in the job text

Keywords

AWS
AWS Data Services
Snowflake
Snowflake Cortex
Snowflake Horizon Catalog
Snowflake Open Catalog
Apache Iceberg
Lakehouse
Enterprise Data Architecture
Data Engineering
Python
PySpark
SQL
ETL/ELT
Batch Processing
Streaming Integration
DataOps
Data Governance
Metadata Management
Data Lineage
Data Observability
IAM/RBAC
Encryption
Responsible AI
Semantic Models
BFSI
Cloud Modernization
Snowpipe
Snowflake Workflows
Snowflake Model Registry

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