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Data & Analytics Architect

HRConnects

Hybrid in Toronto, Ontario • Today

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Full-time

$170000

Adobe Site Reliability Engineer

HRConnects

Hybrid in Toronto, Ontario • Today

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Full-time

$120000

Platform Engineer - AI/ML Infrastructure

HRConnects

Toronto, Ontario • Today

Easy Apply

Full-time

$100000

Chatbot Content Developer

HRConnects

Toronto, Ontario • Today

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Full-time

Depends on Experience

Job Details

Skills

Summary

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:

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.

Must-Have Qualifications:

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.

Nice-to-Have:

Knowledge of BFSI regulatory and security standards.
Experience with Databricks Genie, Workflow, MLflow, and performance optimization.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: PTP4xbc8OzMIXTT
Position Id: 2806
Posted 5 hours ago

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Joanna Gerardo

Recruiter @ HRConnects

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Toronto, Ontario

•

Today

An established global tech company in the B2B data and SaaS space is hiring a full-time, fully remote Data Engineer, open to candidates in Ontario and British Columbia. You'll join a small, high-impact team that partners with business units across the company, from revenue and operations to corporate functions, to solve their data problems. The tech stack spans AWS and Google Cloud Platform and includes BigQuery, dbt, Fivetran, Databricks, Terraform, and Python. This isn't a heads-down pipeline

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