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Added 1 hour ago
NA
Alarm & Service Technician
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- Full-time
Configure customer accounts and mobile applications.
Added 1 hour ago
SM
RQ11843 – Software Developer – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
We are seeking a highly experienced Senior Software Developer with strong expertise in developing, designing, implementing, and maintaining n-tier enterprise applications. The ideal…
Added 1 hour ago
SM
RQ11487 – Software Developer – ETL – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
We are seeking a highly experienced Senior Software Developer – ETL with strong expertise in Azure data technologies, data engineering, ETL development, Microsoft Fabric, Azure Databricks,…
Added 1 hour ago
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RQ00244 – Data Science Developer – Senior
S M Software Solutions Inc
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SM
RQ00241 – Software Developer – ETL – Senior
S M Software Solutions Inc
Toronto, ON
- Internship
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…
Added 1 hour ago
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RQ11858 – Oracle Cloud Integration Specialist – Senior
S M Software Solutions Inc
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RQ11857 – Systems Administrator/Operations Support Specialist – Senior
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S M Software Solutions Inc

RQ00241 – Software Developer – ETL – Senior

Toronto, ON, Canada

Internship

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Job details

Job type: Internship
Apply by: Dec 7, 2026
Posting language: English
Posted: Nov 7, 2026

Original job description

Client: Metrolinx – RQ00241

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

Must Have

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.

Description

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.

Qualifications & Experience

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.

Additional Information

Work Arrangement: Hybrid – 3 days a week onsite.
Public Sector Experience: Preferred but not required.

How to Apply

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)

Please note that we cannot proceed with your submission without the following mandatory documents.

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Additional Information

Email is the best way to reach us.

You have received this message either as a result of contacting our company to express interest in employment or as a result of posting your resume in a location that can be accessed by recruiters or HR specialists, which suggests an interest in being contacted about employment opportunities.

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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 and pipeline reliability while collaborating with technical and business teams to integrate, optimize, deploy, and support production-ready data solutions.

Requirements

Requires significant experience in data engineering, ETL/ELT, software development, or enterprise data integration, with strong Python, SQL, and cloud data platform skills. Candidates should understand Azure data and AI services, scalable pipeline development, data governance and quality, and data preparation for AI, machine learning, and analytics workloads.

Skills

Python
SQL
ETL/ELT
Data Pipeline Development
Data Integration
Data Transformation
API Integration
Azure
Azure Machine Learning
Microsoft Foundry
Machine Learning
Generative AI
Data Modeling
Data Quality
Cloud Data Platforms
Feature Engineering

Visa sponsorship

Not detected in the job text

Keywords

Python
SQL
ETL/ELT
Data Engineering
Data Pipelines
Data Integration
Data Transformation
APIs
Azure
Azure Machine Learning
Microsoft Foundry
Azure AI Foundry
Generative AI
Machine Learning
Feature Engineering
RAG
Data Modeling
Data Quality
Metadata
Data Lineage
Data Governance
Cloud Data Platforms
Enterprise Architecture
Analytics
Business Intelligence
Data Ingestion
Model Training
Inference
Pipeline Monitoring
Data Validation

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