Calian Logo

Base City: 

Toronto - Hybrid

Salary: 

No Salary therefore no Star!

Rating: 

Self-taught: 

Position Type: 

Full-time

Position Keywords: 

Required: 

Bachelor - Computer Science

Experience: 

7 Years Solution Architecture

Other Experience: 

  • Bachelor’s degree or College diploma in Computer Science or equivalent.
  • 7+ years of experience in modern solution architecture.
  • 5+ years of experience in an IT consulting environment, with a recent focus on AI and data analytics.
  • 5+ years of experience in Data & Analytics across various sectors.
  • 5+ years of related experience designing and supporting solutions using technologies such as:
    • C#, MS Copilot, MS Fabric, OpenAI, Azure OpenAI, Azure Data Factory, Azure Data Lake, Azure Synapse Analytics, Azure Databricks, Cosmos DB, Azure Machine Learning Service, Artificial Intelligence including BOT framework, Cognitive Services, Cognitive Search, etc.
  • Strong understanding of existing and emerging Data & AI concepts and technologies, with the ability to translate technical capabilities into business value.
  • Strong hands-on expertise in implementing and architecting scalable cloud solutions.
  • Relevant technical or professional certifications are considered an asset.

What they want you to do: 

At Calian Digital Solutions we understand that choosing the right person for the job makes all the difference, and we are ready to add another passionate person to our ever-growing team of professionals. You’ll be working with some of the leading organizations in Canada and get access to some of the brightest minds in IT. If you are looking for an opportunity that presents a unique challenge with excellent career growth, CDS is the place for you!

Reporting to the Director of Consulting Services, Data & AI, the Solutions Architect will play a pivotal role in the delivery of complex, modern AI, analytics, and data solutions. In this position, you will:

  • Provide technical guidance during presales, POC and envisioning sessions, helping to shape strategies and roadmaps for clients.
  • Design and architect data analytics, GenAI, and machine learning solutions to improve clients’ operational processes.
  • Lead technical implementations teams to develop and deploy data/AI solutions to our customers.
  • Drive the modernization and migration of workloads, ensuring alignment with current technological trends and business requirements.

This role demands a hands-on approach and a deep understanding of both current and emerging technologies to effectively meet and exceed client expectations.

Responsibilities

Pre-sales

  • Assess existing systems and processes to identify gaps and opportunities for improvement.
  • Evaluate and determine appropriate solutions that meet preliminary business requirements gathered from varying stakeholders.
  • Communicate technical concepts and strategies effectively to non-technical stakeholders to ensure alignment on project objectives and expectations.

Solutioning/Design

  • Define requirements for new systems based on detailed analysis of the business’s needs and current technological gaps.
  • Develop scalable and flexible solution designs aligned with business goals, with a focus on leveraging data and AI capabilities.
  • Create and maintain documentation for proposed architecture and preliminary design decisions to ensure clarity and alignment with business objectives.
  • Optimize system design for performance, scalability, and security, focusing on the robustness of data handling and AI processes.

Implementation

  • Collaborate with cross functional teams and other technical stakeholders to guide the development and integration of the designed solutions.
  • Lead the deployment of the solution, ensuring that all elements are correctly implemented and fully functional.
  • Ensure compliance with regulatory requirements and industry best practices during the development phase, especially concerning data security and privacy.
  • Optimize system performance post-deployment to handle data volumes and usage scenarios effectively.
  • Accurately document architecture, final design decisions, configurations, and changes made during deployment.

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