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About the Role

Bridgenext is seeking a Senior Full-Stack Data & AI Engineer to own the complete data lifecycle within a cloud-native Azure ecosystem. This role requires hands-on expertise in Python-based data engineering, analytics, and AI integration using FastAPI, along with the ability to build or support dashboards and data-driven front-end applications. The engineer will own the full data product lifecycle, delivering reusable, governed, high-quality data assets and integrating RESTful APIs.

Responsibilities

Design, develop, and own end-to-end data solutions spanning data ingestion, engineering, modeling, analytics, AI, and front-end consumption
Build and maintain RESTful APIs using FastAPI with authentication, rate limiting, pagination, and error handling
Develop scalable data pipelines and backend services using Python for data ingestion, transformation, and orchestration
Build or support dashboards and data-driven applications (e.g., Power BI, React UI) to enable front-end consumption of data products and KPIs
Design and implement conceptual, logical, and physical data models; build and maintain semantic layers to ensure consistent, governed data access
Deploy and operate containerized data and AI applications on Azure Kubernetes Service (AKS)
Enable ML/LLM use cases including chat, summarization, RAG, agents, and evaluators; prepare and manage data for model training and inference
Integrate data pipelines and applications with Azure OpenAI and other AI services to power intelligent, data-driven features
Deliver analysis-ready datasets, KPIs, and business-ready outputs aligned to stakeholder requirements; collaborate with cross-functional teams and participate in code reviews
Own the full lifecycle of data products: requirements gathering, build, deployment, operational monitoring, and continuous optimization

Requirements

8+ years of professional experience in data engineering, analytics engineering, or full-stack data platform development
Experience building or supporting dashboards and data-driven applications using tools such as Power BI, React, or similar frameworks
Strong experience building RESTful APIs using FastAPI
Expertise in SQL databases (PostgreSQL, MySQL, SQL Server) with strong data modeling skills (conceptual, logical, physical models and semantic layers)
Experience with NoSQL databases such as MongoDB, DynamoDB, or Redis for diverse data storage needs
Hands-on experience deploying containerized data and AI applications on AKS
Experience enabling ML/LLM use cases including data preparation for training/inference, RAG, chat, and summarization
Experience integrating data pipelines with Azure OpenAI and other AI services
Strong proficiency in Python programming with a data product mindset—building reusable, governed, high-quality data assets aligned to business outcomes
Good understanding of Agentic AI frameworks such as LangChain or AutoGen
Exposure to Agent-to-Agent (A2A) communication and agent scaling
Azure data platform experience including Data Factory, Synapse, Purview, Entra ID fundamentals, and app registrations
Knowledge of OAuth2, OIDC, SSO, and SAML configurations; familiarity with data governance and cataloging tools
Solid written, verbal, and presentation communication skills
Strong team and individual player
Maintains composure during all types of situations and is collaborative by nature
High standards of professionalism, consistently producing high quality results
Self-sufficient, independent requiring very little supervision or intervention
Demonstrate flexibility and openness to bring creative solutions to address issues

Skills

Python
FastAPI
Data Engineering
Data Modeling
Analytics
AI Integration
Dashboards
Data-driven Applications
Power BI
React
RESTful APIs
SQL Databases
NoSQL Databases
Containerized Applications
Azure Kubernetes Service (AKS)
ML/LLM Use Cases
Azure OpenAI
Data Pipelines
Agentic AI Frameworks
LangChain
AutoGen
Agent-to-Agent Communication
Azure Data Platform
Data Factory
Synapse
Purview
Entra ID
OAuth2
OIDC
SSO
SAML
Data Governance
Data Cataloging

Location

Greater Toronto Area

Work Type

Hybrid

Experience Level

Senior
8+ years of professional experience

Salary/Compensations

$130,000 - $150,000 CAD annually

About the Company

Bridgenext is a digital consulting services leader that helps clients innovate with intention and realize their digital aspirations by creating digital products, experiences, and solutions around what real people need.
Our global consulting and delivery teams facilitate highly strategic digital initiatives through digital product engineering, automation, data engineering, and infrastructure modernization services, while elevating brands through digital experience, creative content, and customer data analytics services.
Don't just work, thrive. At Bridgenext, you have an opportunity to make a real difference - driving tangible business value for clients, while simultaneously propelling your own career growth.
Our flexible and inclusive work culture provides you with the autonomy, resources, and opportunities to succeed.

Equal Opportunity

Bridgenext is an Equal Opportunity Employer
Canadian citizens and those authorized to work in Canada are encouraged to apply