Data & Analytics Solutions Architect
- Canada
Full-time
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Job details
- Job type
- Full-time
- Posting language
- English
- Posted
Original job description
This role focuses on designing enterprise data platforms, Lakehouse architectures, and AI-driven analytics solutions on AWS.
The ideal candidate has 14+ years of experience in data architecture, Databricks, data engineering, and cloud modernization.
What You Bring
- 14+ years of experience in Enterprise Data Architecture, AWS, Databricks, and Cloud Modernization
- Strong expertise in AWS Data Services, Databricks Genie, Unity Catalog, Delta Lake, Python, PySpark, and SQL
- Experience designing Lakehouse architectures and enterprise data platforms
- Knowledge of Databricks SQL, Workflows, Lakeflow, MLflow, and performance optimization
- Experience with ETL/ELT, batch and streaming pipelines, APIs, and DataOps
- Knowledge of data governance, security, compliance, and responsible AI
- Experience with HLD/LLD, migration planning, architecture reviews, and technical governance
- Understanding of BFSI regulatory and compliance requirements
- Bachelor's degree in Computer Science, Engineering, Information Systems, Data Management, or a related discipline
- Design end-to-end AWS and Databricks data and AI architectures
- Build scalable Lakehouse, data ingestion, and analytics solutions
- Develop AI-driven analytics using Databricks Genie and semantic models
- Establish data governance, security, and observability standards
- Lead cloud modernization, migration, and platform optimization
- Drive architecture reviews, technical standards, and DataOps practices
- Collaborate with engineering teams and stakeholders on solution delivery
- Support technical presentations, effort estimation, and client workshops
- Mentor engineers and develop reusable architecture frameworks
- Certifications in AWS, Databricks, Data Engineering, Enterprise Architecture, Security, or AI/ML
More about this job
Responsibilities
Design end-to-end AWS and Databricks data and AI architectures, including scalable Lakehouse platforms, ingestion pipelines, and analytics solutions. Lead governance, security, modernization, migration, optimization, and architecture standards while collaborating with stakeholders, supporting client engagements, and mentoring engineers.
Requirements
Requires 14+ years of experience in enterprise data architecture, AWS, Databricks, and cloud modernization, with strong expertise in AWS data services, Databricks tools, Python, PySpark, and SQL. Candidates should have experience with Lakehouse design, data pipelines, governance, security, compliance, architecture reviews, and BFSI requirements, plus a bachelor's degree in a related discipline.
Skills
- Enterprise Data Architecture
- AWS
- Databricks
- Cloud Modernization
- AWS Data Services
- Databricks Genie
- Unity Catalog
- Delta Lake
- Python
- PySpark
- SQL
- Lakehouse Architecture
- ETL/ELT
- Data Governance
- DataOps
- Machine Learning
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Consulting
- Management & Leadership
Keywords
- Enterprise Data Architecture
- AWS
- Databricks
- Cloud Modernization
- AWS Data Services
- Databricks Genie
- Unity Catalog
- Delta Lake
- Python
- PySpark
- SQL
- Lakehouse Architecture
- Databricks SQL
- Workflows
- Lakeflow
- MLflow
- ETL/ELT
- Batch Pipelines
- Streaming Pipelines
- APIs
- DataOps
- Data Governance
- Data Security
- Responsible AI
- BFSI
- Migration Planning
- Architecture Reviews
- Performance Optimization
- Data Engineering
- Semantic Models