Hybrid – Toronto, ON, Canada

We are seeking an experienced

Data Science Developer – Senior

Client: Supply Ontario (Public Health Ontario – PHO) | Hybrid – Toronto, ON, Canada

We are seeking an experienced Senior Data Science Developer to design, develop, and support enterprise-scale cloud-based data engineering and advanced analytics solutions for Public Health Ontario (PHO). This role is ideal for professionals with deep expertise in Azure-based data platforms, data engineering, AI/ML integration, analytics, and cloud data architecture.

The successful candidate will lead the design and implementation of scalable data lakes, Lakehouse architectures, automated data pipelines, analytics models, and visualization solutions, while supporting strategic public health initiatives through advanced data science, forecasting, and machine learning capabilities.

Role Snapshot

- Requisition ID: RQ00745
- Job Title: Senior Data Science Developer
- Client: Supply Ontario (Public Health Ontario)
- Work Location: 661 University Ave, Suite 1701, Toronto, ON M5G 1M1, Canada
- Work Arrangement: Hybrid (2 Days Onsite)
- Contract Start Date: August 17, 2026
- Contract End Date: February 12, 2027
- Contract Duration: 130 Business Days
- Schedule: 7.25 Hours/Day | Monday–Friday

Position Summary

Public Health Ontario is expanding its provincial analytics and public health intelligence platform to transform public health data into actionable insights, surveillance capabilities, and informed decision-making.

The Senior Data Science Developer will perform a dual role as both a Data Engineer and Data Science Specialist, developing cloud-native data infrastructure while incorporating advanced analytics and AI capabilities into enterprise data solutions.

This position will contribute to PHO's Azure-based Public Health Data Utility (PHDU), supporting scalable analytics, HealthMap data ingestion, predictive modeling, and modern data engineering initiatives.

Key Responsibilities

- Cloud Data Engineering & Analytics Solutions (45%)
- Design, develop, and maintain cloud-based data engineering solutions.
- Build and optimize enterprise data lakes and Lakehouse architectures.
- Develop automated ETL/ELT pipelines and scalable data workflows.
- Create analytics models, dashboards, and enterprise reporting solutions.




- Ensure solutions comply with enterprise architecture and development standards.
- Design Medallion Architecture for modern data platforms.
- Azure Data Platform Development (30%)

Develop And Maintain Enterprise Solutions Utilizing

- Azure Storage
- Azure Data Lake
- Azure Databricks Lakehouse
- Azure Synapse Analytics
- Azure Data Factory
- Power BI
- Python
- SQL

Support cloud platform operations, performance optimization, troubleshooting, and production deployments.

Data Science & Artificial Intelligence

- Data Science & Artificial Intelligence (15%)
- Identify and prioritize high-value analytics use cases.
- Integrate Machine Learning and Natural Language Processing (NLP) techniques.
- Develop forecasting models and scenario analysis solutions.
- Increase organizational capability for predictive analytics.
- Support HealthMap and Public Health Data Utility initiatives.

Stakeholder Collaboration & Knowledge Transfer

- Stakeholder Collaboration & Knowledge Transfer (10%)
- Collaborate with business partners and technical teams.
- Analyze complex technical issues and recommend effective solutions.
- Prepare comprehensive technical documentation.
- Deliver knowledge transfer sessions for PHO technical staff.
- Support governance, data-sharing, and operational readiness activities.

Key Deliverables

- Enterprise cloud-based data lakes and Lakehouse solutions
- Automated enterprise data pipelines
- Azure-based analytics platforms
- Interactive dashboards and reporting solutions
- Machine Learning and AI-enabled analytics models
- Forecasting and scenario analysis capabilities
- Knowledge transfer documentation and technical training

Required Skills & Experience





Skill / Experience Required Experience developing cloud-based data and analytics platforms Required Designing and implementing Data Lakes and Lakehouse architectures Required Automated ETL/ELT pipelines and enterprise data engineering Required Medallion Architecture implementation Required Azure Storage Required Azure Data Lake Required Azure Databricks Required Azure Synapse Analytics Required Azure Data Factory Required Power BI Required Python Required SQL Required Assessing client technology requirements Required Troubleshooting complex technical environments Required Knowledge transfer documentation and training Required Working within collaborative Agile product teams

Desired Skills

- Strong written and verbal communication skills
- Technical documentation and presentation experience
- Ability to explain complex technical concepts to business stakeholders
- Experience creating enterprise best practices and technical guidelines
- Strong interpersonal and stakeholder management skills
- Experience delivering technical knowledge-transfer sessions

Expected Professional Expertise

The Successful Consultant Will Demonstrate The Ability To
- Apply advanced technical concepts with minimal supervision.
- Lead complex cloud-based data engineering initiatives.
- Mentor technical teams and provide subject matter expertise.
- Deliver enterprise-level data and analytics solutions.
- Recommend strategic technical approaches and architectural improvements.
- Plan, manage, and execute complex technical deliverables.

Preferred Candidate Profile

We are seeking a professional who possesses robust experience across both Data Engineering and Data Science disciplines, including:

- Azure cloud data engineering
- Enterprise data pipeline development
- Lakehouse and Medallion architecture
- Machine Learning and AI integration
- Power BI analytics and visualization
- Python and SQL development
- Public sector project experience (Required)

Additional Information

- Work Model: Hybrid (2 Days Onsite)
- Public Sector Experience: Required
- Location: Toronto, Ontario, Canada

Applications missing any mandatory documents cannot be considered.

If this opportunity is not the right fit for you, we encourage you to share it with qualified professionals experienced in Azure Data Engineering, Data Science, Machine Learning, Data Lake/Lakehouse Architecture, Azure Databricks, Azure Synapse, Power BI, Python, SQL, and Public Sector cloud analytics projects.

📌 Data Science Developer - Senior (Toronto)
🏢 S M Software Solutions
📍 Toronto