Senior Data Science Developers

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Dec 3, 2026
Posting language: English
Posted: Nov 3, 2026

Original job description

Must Haves

Azure Databricks

Python,Azure Data Factory , Power BI

Description

Data Science Developer – Deliverables

The candidates will perform Data Science Developer work by creating, enhancing, maintaining, supporting, and sustaining existing pipelines, analytics models, and data products

Specific Deliverables

Deliverables Expected To Be Produced Could Include

Creating, enhancing, maintaining, and supporting structures for storage of data in formats that are suitable for consumption in analytics solutions.
Automation of data pipelines used to ingest, prepare, transform, and model data for use in analytics products.
Creating, enhancing, maintaining, and supporting dashboards and reports.
Creating, enhancing, maintaining, and supporting analytics environments and implementing new technology to improve performance, simplify architecture patterns, and reduce cloud hosting costs.
Knowledge transfer sessions and documentation for technical staff related to architecting, designing, and implementing continuous improvement enhancements to analytics solutions. These sessions will be held as needed and on a case by case basis that involve walkthroughs of documentation, code, and environment setups.

Skills

Experience and Skill Set Requirements

Data Science Developer – Evaluation Criteria

Data Storage and Preparation – 35%

The candidate must demonstrate their experience with Azure Storage, Azure Data Lake, Azure Databricks Lakehouse, and Azure Synapse structures in real world implementations

Data Pipelines – 35%

The candidate must demonstrate their experience with automating data pipelines using appropriate Microsoft Azure Platform/Technologies (SQL,Python, Databricks and Azure Data Factory)

Data Analytics – 15%

The candidate must demonstrate their experience with Power BI reports and dashboards

Knowledge Transfer – 15%

The candidate must demonstrate experience in conducting knowledge transfer sessions and building documentation for technical staff related to architecting, designing, and implementing end to end analytics solutions

Hybrid:3 days per week in the office

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More about this job

Responsibilities

Create, enhance, maintain, and support data storage structures, automated data pipelines, analytics models, dashboards, reports, and analytics environments. Improve analytics performance and architecture, reduce cloud hosting costs, and provide technical documentation and knowledge-transfer sessions.

Requirements

Candidates must demonstrate real-world experience with Azure Storage, Azure Data Lake, Databricks Lakehouse, and Azure Synapse. They must also have experience automating pipelines with SQL, Python, Databricks, and Azure Data Factory, developing Power BI reports and dashboards, and documenting and transferring knowledge about end-to-end analytics solutions.

Skills

Azure Storage
Azure Data Lake
Azure Databricks
Databricks Lakehouse
Azure Synapse
Azure Data Factory
Python
SQL
Power BI
Data Pipeline Automation
Data Modeling
Dashboard Development
Analytics Solutions
Technical Documentation
Knowledge Transfer
Cloud Cost Optimization

Visa sponsorship

Not detected in the job text

Keywords

Azure Storage
Azure Data Lake
Azure Databricks
Databricks Lakehouse
Azure Synapse
Azure Data Factory
Python
SQL
Power BI
Data Science
Data Storage
Data Preparation
Data Pipelines
Pipeline Automation
Data Ingestion
Data Transformation
Data Modeling
Analytics Models
Data Products
Dashboards
Reports
Analytics Environments
Cloud Hosting Costs
Architecture Design
Performance Improvement
Continuous Improvement
Technical Documentation
Knowledge Transfer
End-to-End Analytics Solutions

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