RQ00241 – Software Developer – ETL – Senior
- Toronto, ON, Canada
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Original job description
We are seeking a Senior Software Developer – ETL with significant hands-on experience in designing, developing, and maintaining scalable, production-grade data pipelines and integration solutions. The ideal candidate will have strong expertise in Python, SQL, ETL/ELT, APIs, data integration, data transformation, and cloud-based data platforms, along with a strong understanding of the Azure data and AI ecosystem, Azure Machine Learning, and Microsoft Foundry/Azure AI Foundry. The successful candidate will build reusable data services and pipelines to support enterprise AI, Machine Learning, Generative AI, analytics, and data initiatives while ensuring data quality, scalability, reliability, and performance.
Role Snapshot
- Job Title: RQ00241 – Software Developer – ETL – Senior
- Client: Metrolinx
- Work Location: 277 Front Street West, Toronto, Ontario, Canada
- Work Arrangement: Hybrid – 3 Days per Week Onsite
- Estimated Start Date: November 23, 2026
- Estimated End Date: May 23, 2027
- Business Days: 130.00
- Hours: 7.25 hours per day
- Significant hands-on experience designing and developing scalable, production-grade data pipelines for AI/ML and Generative AI workloads, including data ingestion, transformation, feature engineering, training and inference datasets, RAG/grounding data, and AI/ML pipeline integration.
- Advanced hands-on expertise in Python, SQL, ETL/ELT, APIs, data integration and transformation, and cloud-based data platforms, applying strong software engineering practices to build reliable, scalable, maintainable, and production-ready data solutions.
- Strong working knowledge of the Azure data and AI ecosystem, Azure Machine Learning, and Microsoft Foundry/Azure AI Foundry, with an understanding of ML pipelines, feature engineering, model training/testing, inference, monitoring, and the data requirements needed to support reliable enterprise AI/ML solutions.
The Senior Software Developer – ETL will design, build, and maintain scalable data pipelines, integrations, and reusable data services that enable enterprise AI, analytics, and data initiatives.
The role will help improve access to trusted data across enterprise systems, operationalize data architecture and integration patterns, and reduce the time and effort required to onboard data for new AI and analytics use cases.
Key Responsibilities
- Design, develop, test, and maintain ETL/ELT pipelines and data integration solutions across enterprise data sources.
- Build reusable data pipelines, services, and integration components that can support multiple AI and analytics use cases.
- Ingest, transform, and prepare structured and unstructured data for analytics, AI, and machine learning workloads.
- Implement data architecture, modelling, and integration patterns established by enterprise architecture.
- Integrate data across cloud platforms, databases, applications, APIs, and enterprise systems.
- Design solutions that support scalability, reliability, performance, monitoring, and maintainability.
- Implement data quality and validation controls to improve the reliability of data provided to downstream consumers.
- Work with Data Architects, AI/ML Engineers, Data Scientists, product teams, and business stakeholders to translate data requirements into production-ready solutions.
- Optimize existing pipelines and integration processes to reduce duplication and accelerate onboarding of new data sources.
- Support deployment, troubleshooting, documentation, and ongoing improvement of enterprise data solutions.
- Degree in Computer Science, Information Systems, Engineering, Data/Analytics, or a related discipline, or equivalent experience.
- Significant experience in data engineering, ETL/ELT development, software development, or enterprise data integration.
- Demonstrated experience designing and developing scalable data pipelines and integration solutions.
- Strong programming and SQL skills, with experience working with modern data engineering frameworks and cloud-based data platforms.
- Experience integrating data through databases, APIs, file-based sources, and enterprise applications.
- Knowledge of data modelling, data quality, metadata, lineage, security, and data governance concepts.
- Experience supporting data platforms used for AI, machine learning, advanced analytics, and business intelligence.
- Strong analytical, troubleshooting, communication, and collaboration skills.
- Work Arrangement: Hybrid – 3 days a week onsite.
- Public Sector Experience: Preferred but not required.
If you are interested and your profile matches the requirements, kindly submit the following mandatory documents to hrsmss@smsoftconsulting.com by Monday, November 9, 2026, at 8:00 AM EST.
Mandatory Documents
- Updated Resume in Word format (Mandatory)
- Skills Matrix and References (Mandatory)
- Expected Hourly Rate (Mandatory)
- Visa Status (Mandatory)
- LinkedIn ID (Mandatory)
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Additional Information
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More about this job
Responsibilities
Design, develop, and maintain scalable ETL/ELT pipelines, integrations, and reusable data services for enterprise AI, analytics, and data initiatives. Ensure data quality, reliability, performance, and maintainability while collaborating with technical and business teams and supporting deployment and ongoing improvement.
Requirements
Requires significant experience in data engineering, ETL/ELT, software development, or enterprise data integration, with strong Python, SQL, API, and cloud data platform skills. Candidates should understand Azure data and AI services, scalable pipeline design, data quality and governance, and data preparation for AI/ML workloads; a relevant degree or equivalent experience is required.
Skills
- Python
- SQL
- ETL/ELT
- Data Pipelines
- Data Integration
- APIs
- Azure
- Azure Machine Learning
- Microsoft Foundry
- Data Transformation
- Data Modeling
- Data Quality
- Machine Learning
- Generative AI
- Cloud Data Platforms
- Data Governance
Visa sponsorship
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Categories
- Software
- Technology
- Data & Analytics
- Government & Public Sector
Keywords
- Python
- SQL
- ETL/ELT
- Data Engineering
- Data Pipelines
- Data Integration
- APIs
- Azure
- Azure Machine Learning
- Microsoft Foundry
- Azure AI Foundry
- Generative AI
- Machine Learning
- Feature Engineering
- RAG
- Cloud Data Platforms
- Data Transformation
- Data Modeling
- Data Quality
- Metadata
- Data Lineage
- Data Governance
- Data Security
- Enterprise Architecture
- Analytics
- Business Intelligence
- Structured and Unstructured Data
- Model Training
- Inference
- Pipeline Monitoring