Data Engineer / Data Science Specialist/Senior Data Science Developer – Azure Data Platform (Public Sector) in GTA-Hybrid

Client: Confidential Public Sector Organization

Compensation : $60.00-$75.00 per hour

Stafingo is Hiring: Data Engineer / Data Science Specialist (Azure Data Platform)

Stafingo is partnering with a leading public sector organization in the Greater Toronto Area (GTA) to identify an experienced Data Engineer / Data Science Specialist who can help advance enterprise analytics capabilities, cloud data infrastructure, and AI-driven decision support initiatives.

This role combines modern cloud data engineering, analytics platform development, and applied data science .

This is an exciting opportunity for a senior-level professional who enjoys working across data engineering, analytics, machine learning, and cloud platforms to deliver impactful solutions supporting population-level insights and evidence-based decision-making.

Role Overview

The Data Engineer / Data Science Specialist will build and enhance the cloud-based data foundation supporting advanced analytics initiatives. This individual will work with cross-functional teams to design, develop, and operationalize:

- Data lake and Lakehouse architectures
- Analytics-ready datasets
- Data models and dashboards
- AI/ML use cases
- Forecasting and scenario analysis solutions

The successful candidate will contribute to building sustainable analytics capabilities through strong engineering practices, documentation, and knowledge transfer.

Key Responsibilities

- Design, develop, and maintain scalable cloud-based data pipelines supporting analytics products and advanced analytical solutions.
- Build and optimize Azure-based data platforms, including data lakes, Lakehouse structures,



and analytics environments.
- Develop automated ingestion, transformation, and processing workflows using modern data engineering tools.
- Create analytics-ready datasets to support reporting, modelling, and decision-support initiatives.

Data Analytics & Data Science Enablement

- Collaborate with analytics and business teams to identify and prioritize high-value data and AI/ML use cases.
- Support machine learning initiatives including forecasting, predictive modelling, and scenario analysis.
- Apply AI techniques such as machine learning and natural language processing (NLP) to enhance analytical capabilities.
- Develop models, dashboards, and visualizations that support evidence-based decisions.
- Design and implement solutions using:
- Power BI
- Python
- SQL
- Support data acquisition, integration, governance, and secure data-sharing processes.
- Troubleshoot complex technical issues across data pipelines, integrations, and analytics solutions.

Collaboration & Knowledge Transfer

- Work closely with technical teams, business stakeholders, and product teams to deliver analytics solutions.
- Participate in architecture discussions, technical reviews, and solution design activities.
- Prepare technical documentation, guidelines, and knowledge-transfer materials.
- Conduct knowledge-transfer sessions to support long-term sustainability of developed solutions.

Required Qualifications





Strong experience designing and implementing cloud-based data and analytics solutions.

Hands-on experience building and maintaining

- Azure Data Lake / Lakehouse platforms
- Automated data pipelines
- Data transformation frameworks
- Dashboards and reporting solutions

Advanced experience with modern Azure data technologies

- Power BI
- Python
- SQL

Experience with

- Medallion architecture
- Cloud analytics platforms
- Solid analytical problem-solving skills with experience resolving complex technical challenges.
- Experience working with stakeholders to understand requirements and translate business needs into technical solutions.
- Experience creating technical documentation and conducting knowledge-transfer sessions.
- Ability to work independently while collaborating effectively within multidisciplinary teams.

Preferred / Nice-to-Have Skills

- Experience supporting public sector, healthcare, or regulated environments.
- Experience with machine learning, NLP, forecasting, or predictive analytics.
- Experience developing AI-enabled analytics solutions.
- Experience with data governance, data-sharing frameworks, and enterprise analytics platforms.
- Experience mentoring team members and providing technical guidance.

Ideal Candidate Profile

We are looking for a senior professional who can:

- Lead complex data engineering initiatives with minimal supervision
- Bridge the gap between data engineering and data science
- Apply AI/ML techniques to real-world business challenges
- Communicate effectively with technical and non-technical stakeholders
- Deliver high-quality solutions in a fast-paced public sector environment

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📌 Senior Data Scientist (Toronto)
🏢 StafinGo
📍 Toronto