Azure Databricks Solutions Architect

N2P Systems is seeking an experienced Azure Databricks 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 Azure, Azure Databricks and Azure Data Services 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 architecture and modernization of enterprise-scale data, analytics, and AI platforms using Microsoft Azure and Databricks. This position requires extensive experience in enterprise data architecture, cloud engineering, and modern Lakehouse solutions.

The successful candidate will define end-to-end technical architectures, establish enterprise governance standards, and guide the implementation of scalable, secure, and high-performance data platforms. The role also involves technical consulting, stakeholder engagement, architecture governance, and supporting large-scale 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 identify requirements across data, analytics, AI, and cloud transformation initiatives.

• Define comprehensive architectures for enterprise data, analytics, and AI platforms built on Azure and Databricks.

• Design scalable and secure Lakehouse solutions leveraging Azure Data Services, Databricks, Delta Lake, and Unity Catalog.

• Architect enterprise data ingestion, integration, batch processing, streaming, and engineering solutions.

• Develop AI-enabled analytics capabilities using Databricks Genie, semantic models, and controlled data access frameworks.

• Establish platform-wide standards for data governance, security, metadata, lineage, observability, and responsible AI.

• Lead cloud migration, data platform modernization, and Azure transformation initiatives.

• Define architecture standards, reusable frameworks, engineering practices, and DataOps delivery approaches.

• Provide technical direction throughout solution architecture, implementation, testing, migration, deployment, and production support.

• Conduct architecture assessments, identify technical risks and dependencies, and recommend appropriate mitigation approaches.

• Improve platform performance, operational reliability, and infrastructure cost efficiency across Azure and Databricks environments.

• Coordinate with data engineering, AI, architecture, platform, and client teams to deliver enterprise-grade solutions.

• Contribute to solution development, RFP responses, effort estimation, technical presentations, and client workshops.

• Mentor architects and engineers while supporting technical capability development, assessments, and knowledge sharing.

• Create reusable accelerators, reference architectures, implementation frameworks, and engineering best practices for Azure Databricks and AI platforms.

Required Skills & Qualifications:

• At least 14 years of experience across enterprise data architecture, Azure data platforms, Databricks, data engineering, and cloud modernization.

• Proven experience designing enterprise solutions using Azure and Databricks across the complete Data-to-Insights lifecycle.

• Strong hands-on expertise in Azure Data Services, Azure Databricks, Delta Lake, Unity Catalog, Python, PySpark, and SQL.

• Demonstrated experience designing and implementing Lakehouse architectures, enterprise data platforms, and modern analytics solutions.

• Strong understanding of the Databricks Data Intelligence Platform and its enterprise capabilities.

• Expertise in data engineering, including ETL/ELT, batch and streaming integration, APIs, orchestration, data quality, metadata, 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, 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:

• Hands-on experience with Databricks Genie and natural language analytics.

• Familiarity with Databricks SQL, Workflows, Lakeflow, MLflow, Serverless, and advanced performance optimization.

• Experience developing AI-enabled analytics solutions using semantic models and governed data access patterns.

• Exposure to responsible AI practices and enterprise AI implementation.

• Professional certifications in Azure Solutions Architecture, Azure Data Engineering, Databricks, Data Management, Enterprise Architecture, Security, or AI/ML.