Data & Analytics Architect
- Toronto, ON, Canada
Salary range: $150000-170000 · Full-time
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Job details
- Pay
- Salary range: $150000-170000
- Job type
- Full-time
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- Posting language
- English
- Posted
Original job description
Are you passionate about shaping the future of data and AI solutions? Join us as a Data & Analytics Architect and lead transformative projects that elevate enterprise data platforms to new heights. This is your chance to make a real impact by designing innovative, scalable, and secure data architectures that drive strategic decision-making and enable cutting-edge AI experiences.
Overview
We’re seeking an experienced senior professional to lead the design and implementation of enterprise data, analytics, and AI platforms using AWS and Databricks. This hybrid role combines hands-on architecture, cloud modernization, data engineering, governance, and client-facing solution leadership. If you thrive on solving complex data challenges and guiding teams through impactful digital transformations, this is the role for you.
Start Date: ASAP
Location: Toronto, ON -Hybrid
Salary range: $150000-170000
Key Responsibilities
Overview
We’re seeking an experienced senior professional to lead the design and implementation of enterprise data, analytics, and AI platforms using AWS and Databricks. This hybrid role combines hands-on architecture, cloud modernization, data engineering, governance, and client-facing solution leadership. If you thrive on solving complex data challenges and guiding teams through impactful digital transformations, this is the role for you.
Start Date: ASAP
Location: Toronto, ON -Hybrid
Salary range: $150000-170000
Key Responsibilities
- Collaborate with business and technology stakeholders to understand requirements related to data, analytics, AI, and cloud modernization.
- Architect end-to-end solutions on AWS and Databricks, including secure, scalable Lakehouse platforms featuring Delta Lake and Unity Catalog.
- Design data ingestion, integration, and AI-enabled analytics solutions incorporating streaming, batch processing, semantic models, and natural-language analytics.
- Lead the development of high-level and low-level architecture designs, assess non-functional aspects, and support migration planning and production readiness.
- Establish standards for security, governance, metadata management, observability, and responsible AI practices.
- Drive modernization initiatives, addressing scalability, reliability, and compliance across cloud environments.
- Conduct architecture reviews, identify risks, and guide mitigation strategies.
- Optimize performance, cost-efficiency, and serverless compute across AWS and Databricks platforms.
- Support solution proposals, client workshops, and deliver technical presentations.
- Mentor team members and develop reusable frameworks, accelerators, and reference architectures to ensure best practices.
- 14+ years in enterprise data architecture, AWS data platforms, Databricks, or cloud modernization.
- Hands-on experience with AWS data services, Databricks, Delta Lake, Python, PySpark, and SQL.
- Proven expertise designing Lakehouse architectures, enterprise data platforms, and modern analytical solutions.
- Deep understanding of ETL/ELT, streaming, APIs, data governance, and DataOps.
- Experience with security, privacy, IAM/RBAC, encryption, and responsible AI practices.
- Ability to support client-facing discussions, RFPs, and technical leadership.
- Bachelor's degree in a relevant discipline; certifications are preferred.
- Knowledge of BFSI regulatory and security standards.
- Experience with Databricks Genie, Workflow, MLflow, and performance optimization.
More about this job
Responsibilities
Lead the architecture and implementation of secure, scalable enterprise data, analytics, and AI platforms on AWS and Databricks, including Lakehouse solutions, data pipelines, and cloud modernization. Establish governance and security standards, optimize performance and cost, guide architecture reviews and migration readiness, and support clients and teams through workshops, proposals, and mentorship.
Requirements
Requires 14+ years of experience in enterprise data architecture, AWS data platforms, Databricks, or cloud modernization, with hands-on expertise in AWS services, Databricks, Delta Lake, Python, PySpark, and SQL. Candidates should have strong Lakehouse, data engineering, governance, security, and DataOps experience, client-facing technical leadership skills, and a bachelor's degree; certifications are preferred.
Skills
- AWS
- Databricks
- Delta Lake
- Unity Catalog
- Python
- PySpark
- SQL
- Data Architecture
- Lakehouse Architecture
- ETL/ELT
- Streaming Data
- Data Governance
- DataOps
- Cloud Modernization
- IAM/RBAC
- Responsible AI
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Consulting
- Management & Leadership
Keywords
- AWS
- Databricks
- Delta Lake
- Unity Catalog
- Python
- PySpark
- SQL
- Lakehouse
- Enterprise Data Platforms
- Data Architecture
- Data Engineering
- ETL/ELT
- Streaming
- Batch Processing
- Semantic Models
- Natural-Language Analytics
- Data Governance
- Metadata Management
- DataOps
- Cloud Modernization
- IAM/RBAC
- Encryption
- Responsible AI
- Serverless Compute
- Databricks Genie
- Databricks Workflows
- MLflow
- BFSI
- Performance Optimization
- Architecture Reviews