Salary
$65 - $70 / hour
Location
Toronto, ON
Posted
Jul 9, 2026
Role overview
Job Title: Data Science Developer - Senior
Department: Solution Delivery
Location: Toronto, Ontario
Work Model: Onsite
Duration: 6 Months
Shortlist Date: 2026-07-14, 10:00 a.m.
Supplier Comments / MSP Notes
Must Haves
- 5+ years of experience working in Azure environments.
- 5+ years of Data Engineering experience using:
- Azure Data Factory (ADF)
- Azure Databricks
- 5+ years of programming experience with:
- Python
- SQL
Description / Responsibilities / Skills
Role Overview
The Senior Data Science Developer will participate in product delivery teams responsible for designing, building, modernizing, and supporting cloud-based data and analytics solutions.
The primary focus is migrating existing Azure Synapse and Azure Data Factory workloads to modern Databricks Lakehouse architectures while establishing reusable frameworks and engineering standards.
Responsibilities
Data Engineering & Solution Development
- Analyze system requirements.
- Design and implement cloud-based data and analytics products.
- Architect data solutions that conform to enterprise standards.
- Build and maintain cloud-native data platforms.
Lakehouse & Data Platform Development
- Design and maintain:
- Azure Data Lakes
- Databricks Lakehouse structures
- Analytics models
- Automated data pipelines
- Implement scalable and maintainable data architectures.
Data Migration
- Support migration from:
- Azure Synapse Analytics
- Azure Data Factory
- Modernize:
- Stored procedures
- BI views
- ADLS Parquet files
- Implement Databricks-based solutions using:
- Delta Lake
- Native orchestration capabilities
Framework Development
- Develop reusable engineering frameworks.
- Standardize data pipeline development processes.
- Support engineering best practices.
Collaboration & Support
- Work with IT teams and business stakeholders.
- Resolve technical and operational issues.
- Participate in code reviews.
- Conduct knowledge transfer sessions.
- Support Agile product teams.
General Skills
- Experience with multiple cloud-based data and analytics platforms.
- Azure-focused data engineering experience.
- Experience designing and maintaining:
- Data Lakes
- Lakehouses
- Data Pipelines
- Analytics Models
- Strong Azure Data Factory and Databricks expertise.
- Experience implementing Medallion Architecture.
- Knowledge of Databricks Unity Catalog (asset).
- Strong Python and SQL development skills.
- CI/CD experience.
- GitHub code management experience.
- Code review and peer review experience.
- IT needs assessment and solution recommendation experience.
- Complex problem-solving and troubleshooting abilities.
- Knowledge transfer experience.
- Agile project experience.
Technology Stack
Cloud & Data Platforms
- Azure Storage
- Azure Data Lake Storage (ADLS)
- Azure Databricks
- Databricks Lakehouse
- Azure Synapse Analytics
- Azure Data Factory (ADF)
Programming & Analytics
- Python
- SQL
- Power BI
Source Control & DevOps
- GitHub
- CI/CD Pipelines
Key Technical Areas
Data Engineering
- Data pipeline design and development
- Data transformation
- ETL/ELT development
- Lakehouse architecture
- Data migration and modernization
Databricks
- Databricks Lakehouse
- Delta Lake
- Medallion Architecture
- Unity Catalog
- Workflow orchestration
Azure
- Azure Data Factory
- Azure Synapse
- Azure Storage
- Azure Data Lake
Analytics
- Data modelling
- Data preparation
- BI enablement
- Reporting support
- Power BI integration