AWS Snowflake Solutions Architect
- Toronto, ON, Canada
Full-time
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Job details
- Job type
- Full-time
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- Posting language
- English
- Posted
Original job description
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.
- 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.
- 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.
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
Categories
- Technology
- Data & Analytics
- Software
- Consulting
- Management & Leadership
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