Data & Analytics Solutions Architect - AI platforms, AWS, Databricks
- Toronto, ON, Canada
Full-time
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Job details
- Job type
- Full-time
- Apply by
- Experience
- 14+ years of experience in enterprise data architecture, AWS data platforms, Databricks, data engineering, and cloud modernization.
- Posting language
- English
- Posted
Original job 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
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Engage business and technology stakeholders to understand data, analytics, AI, cloud, and modernization requirements.
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Define end-to-end architecture for AWS and Databricks-based data, analytics, and AI platforms.
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Design secure, scalable, and high-performance Lakehouse solutions using AWS services, Databricks, Delta Lake, and Unity Catalog.
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Architect data ingestion, integration, batch, streaming, data engineering, semantic, analytics, and AI solutions.
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Design AI-enabled analytics experiences using Databricks Genie, semantic models, natural-language analytics, and governed data access.
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Lead architecture definition, HLD/LLD preparation, non-functional assessments, migration planning, technical governance, and production readiness.
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Establish standards for security, governance, metadata, lineage, observability, responsible AI, and DataOps delivery.
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Lead data-platform modernization and cloud migration initiatives while addressing scalability, reliability, and compliance.
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Conduct architecture reviews, identify risks and dependencies, and guide teams on practical mitigation strategies.
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Drive performance, reliability, serverless-compute, and cost optimization across AWS and Databricks environments.
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Support solutioning, RFP responses, effort estimation, technical presentations, and workshops.
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Mentor architects and engineers and develop reusable accelerators, reference architectures, implementation frameworks, and best practices.
What You Bring
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14+ years of experience in enterprise data architecture, AWS data platforms, Databricks, data engineering, and cloud modernization.
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Hands-on expertise with AWS data services, Databricks, Databricks Genie, Unity Catalog, Delta Lake, Python, PySpark, and SQL.
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Strong knowledge of the Databricks Data Intelligence Platform, including Databricks SQL, Workflows, Lakeflow, MLflow, serverless compute, and performance optimization.
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Experience designing Lakehouse architectures, enterprise data platforms, data products, warehouses, semantic layers, and modern analytics solutions.
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Expertise in ETL/ELT, batch and streaming integration, APIs, orchestration, data quality, metadata management, lineage, observability, and DataOps.
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Experience implementing IAM/RBAC, encryption, privacy, masking, retention, auditability, governance, and responsible AI controls.
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Experience supporting cloud transformation, architecture governance, RFPs, estimates, and client-facing solution discussions.
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Understanding of financial services regulatory, security, privacy, resilience, and audit requirements.
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Bachelor's degree in a relevant discipline. AWS, Databricks, data engineering, architecture, security, or AI/ML certifications are preferred.
More about this job
Responsibilities
Define and lead end-to-end AWS and Databricks architectures for enterprise data, analytics, and AI platforms, including modernization, migration, governance, and production readiness. Guide implementation teams, optimize platform performance and cost, advise stakeholders, and support solution consulting, technical leadership, and reusable architecture development.
Requirements
Requires 14+ years of experience in enterprise data architecture, AWS, Databricks, data engineering, and cloud modernization, with hands-on expertise in relevant AWS and Databricks services, Python, PySpark, and SQL. A bachelor's degree in a relevant discipline is required; experience with financial services controls is expected, while relevant technical certifications are preferred.
Skills
- AWS
- Databricks
- Data Architecture
- Lakehouse Architecture
- Data Engineering
- Python
- PySpark
- SQL
- Delta Lake
- Unity Catalog
- Databricks Genie
- Cloud Modernization
- Data Governance
- Batch and Streaming Integration
- DataOps
- Responsible AI
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Consulting
- Management & Leadership
Keywords
- AWS
- Databricks
- Databricks Genie
- Databricks SQL
- Unity Catalog
- Delta Lake
- Lakehouse
- Python
- PySpark
- SQL
- Lakeflow
- Workflows
- MLflow
- Serverless Compute
- Data Architecture
- Data Engineering
- Data Products
- Semantic Models
- ETL/ELT
- Batch Processing
- Streaming Integration
- Data Governance
- Metadata Management
- Data Lineage
- Observability
- DataOps
- Responsible AI
- Cloud Migration
- IAM/RBAC
- Financial Services