Data & Analytics Solutions Architect - AI platforms, AWS, Databricks
Senior Data & Analytics Solutions Architect designing enterprise data, analytics, and AI platforms on AWS and Databricks (Lakehouse, Delta Lake, Unity Catalog). The role blends hands-on architecture, cloud modernization, governance, mentoring, and client-facing solution consulting like RFPs and workshops.
- Compensation
- Not disclosed
- Location
- Toronto, Canada
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 14+ years
- Category
- Architecture
- Posted
Skills
Must have
- 14+ years of experience in enterprise data architecture, AWS data platforms, Databricks, data engineering, and cloud modernization
- Hands-on expertise with AWS data services, Databricks, Databricks Genie, Unity Catalog, Delta Lake, Python, PySpark, and SQL
- Strong knowledge of the Databricks Data Intelligence Platform (Databricks SQL, Workflows, Lakeflow, MLflow, serverless compute, performance optimization)
- Experience designing Lakehouse architectures, enterprise data platforms, data products, warehouses, semantic layers, and modern analytics solutions
- Expertise in ETL/ELT, batch and streaming integration, APIs, orchestration, data quality, metadata management, lineage, observability, and DataOps
- Experience implementing IAM/RBAC, encryption, privacy, masking, retention, auditability, governance, and responsible AI controls
- Experience supporting cloud transformation, architecture governance, RFPs, estimates, and client-facing solution discussions
- Understanding of financial services regulatory, security, privacy, resilience, and audit requirements
- Bachelor's degree in a relevant discipline
Nice to have
- AWS, Databricks, data engineering, architecture, security, or AI/ML certifications
Full description
**Data & Analytics Solutions Architect - AI platforms, AWS, Databricks
The Opportunity**
We are hiring a senior Data & Analytics Solutions Architect to lead the design of enterprise data, analytics, and AI platforms using AWS and Databricks. This role combines hands-on architecture, cloud modernization, data engineering, governance, technical leadership, and solution consulting. You will define architecture direction, guide implementation teams, and help organizations move from legacy environments to secure, scalable, production-ready platforms.
What You Will Do
- Engage business and technology stakeholders to understand data, analytics, AI, cloud, and modernization requirements.
- Define end-to-end architecture for AWS and Databricks-based data, analytics, and AI platforms.
- Design secure, scalable, and high-performance Lakehouse solutions using AWS services, Databricks, Delta Lake, and Unity Catalog.
- Architect data ingestion, integration, batch, streaming, data engineering, semantic, analytics, and AI solutions.
- Design AI-enabled analytics experiences using Databricks Genie, semantic models, natural-language analytics, and governed data access.
- Lead architecture definition, HLD/LLD preparation, non-functional assessments, migration planning, technical governance, and production readiness.
- Establish standards for security, governance, metadata, lineage, observability, responsible AI, and DataOps delivery.
- Lead data-platform modernization and cloud migration initiatives while addressing scalability, reliability, and compliance.
- Conduct architecture reviews, identify risks and dependencies, and guide teams on practical mitigation strategies.
- Drive performance, reliability, serverless-compute, and cost optimization across AWS and Databricks environments.
- Support solutioning, RFP responses, effort estimation, technical presentations, and workshops.
- Mentor architects and engineers and develop reusable accelerators, reference architectures, implementation frameworks, and best practices.
**What You Bring
- 14+ years of experience in enterprise data architecture, AWS data platforms, Databricks, data engineering, and cloud modernization.
- Hands-on expertise with AWS data services, Databricks, Databricks Genie, Unity Catalog, Delta Lake, Python, PySpark, and SQL.
- Strong knowledge of the Databricks Data Intelligence Platform, including Databricks SQL, Workflows, Lakeflow, MLflow, serverless compute, and performance optimization.