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Astra-North Infoteck Inc. ~ Conquering today’s challenges, achieving tomorrow’s vision!
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Astra-North Infoteck Inc. ~ Conquering today’s challenges, achieving tomorrow’s vision!

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: Nov 12, 2026
Experience: 14+ years of experience in enterprise data architecture, AWS data platforms, Databricks, data engineering, and cloud modernization.
Posting language: English
Posted: Oct 13, 2026

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

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.
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. AWS, Databricks, data engineering, architecture, security, or AI/ML certifications are preferred.

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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

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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

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