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RQ11673 – Report Developer – Junior
S M Software Solutions Inc
Toronto, ON
- Internship
We are seeking a Junior Report Developer / Data Engineer with experience in developing, implementing, and maintaining enterprise data solutions using modern Azure cloud technologies. The…
Added 2 hours ago
DA
Quality Engineer
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- Full-time
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S M Software Solutions Inc

RQ11673 – Report Developer – Junior

Toronto, ON, Canada

Internship

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Job details

Job type: Internship
Apply by: Dec 6, 2026
Posting language: English
Posted: Nov 6, 2026

Original job description

Client: Ministry of Public and Business Service Delivery and Procurement – RQ11673

We are seeking a Junior Report Developer / Data Engineer with experience in developing, implementing, and maintaining enterprise data solutions using modern Azure cloud technologies. The ideal candidate will have hands-on experience with Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Databricks, Delta Lake, Lakehouse architecture, Python, SQL, and Spark-based data processing frameworks. The successful candidate will support the Government of Ontario's Ontario Data Platform (ODP) initiative by developing scalable data pipelines, implementing data integration solutions, optimizing data processing workflows, and ensuring data quality, security, governance, and operational efficiency.

Role Snapshot

Job Title: RQ11673 – Report Developer – Junior
Client: Ministry of Public and Business Service Delivery and Procurement
Work Location: 222 Jarvis Street, Toronto, Ontario, Canada
Work Arrangement: Onsite – 5 Days per Week
Estimated Start Date: September 28, 2026
Estimated End Date: March 31, 2027
Business Days: 133.00
Extension: Probable after the initial mandate
Hours: 7.25 hours per day
Security Level: No Clearance Required

Must Have

Qualifications

Degree or diploma in Computer Science, Software Engineering, Information Technology, or a related field.
Experience developing data solutions using Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Databricks, Delta Lake, and Lakehouse architecture principles.
Experience working with Azure DevOps, Git, CI/CD pipelines, and automated deployment practices.
Strong proficiency in Python, SQL, and Spark-based data processing frameworks.
Knowledge of data governance, security, privacy, and access control principles.
Experience with REST APIs, application integration patterns, and automation frameworks.

Description

Role Overview

The Government of Ontario is undertaking a large-scale Data & AI transformation initiative, with the Ontario Data Platform (ODP) serving as the enterprise technology ecosystem for data-driven decision-making, analytics, and artificial intelligence.

ODP provides a modern and scalable data environment supporting data ingestion, storage, processing, governance, quality, marketplace capabilities, and advanced analytics across ministries and government organizations.

We are seeking a Data Engineer / Software Developer to support the design, development, and operation of enterprise data solutions on the Ontario Data Platform. The successful candidate will work with modern cloud technologies, including Databricks, Azure Data Factory (ADF), and Azure Data Lake Storage (ADLS), to build scalable data pipelines, enable analytics use cases, and support the delivery of high-quality data products across government.

Key Responsibilities

Data Engineering & Pipeline Development
Design, develop, and maintain scalable batch and near real-time data pipelines using Azure Data Factory (ADF), Databricks, and related cloud technologies.
Develop data ingestion frameworks to onboard data from various source systems into the Ontario Data Platform.
Build and optimize ETL/ELT processes to transform, cleanse, and prepare data for analytics and reporting.
Implement data validation, monitoring, and reconciliation processes to ensure data quality and reliability.
Databricks Development
Develop and maintain notebooks, workflows, and data processing jobs using Databricks.
Build data transformation pipelines leveraging Spark and Databricks Lakehouse architecture.
Support the implementation of medallion architecture patterns (Bronze, Silver, Gold).
Monitor and troubleshoot Databricks jobs, workflows, and performance issues.
Develop and manage Delta Lake tables and optimize data processing workloads for performance and scalability.
Data Storage & Integration
Design and manage data solutions utilizing Azure Data Lake Storage (ADLS).
Collaborate with source system teams to establish secure and efficient data integration patterns.
Implement data partitioning, optimization, and archival strategies to improve performance and scalability.
Support metadata management, data cataloguing, and governance initiatives.
Software Development & Automation
Develop reusable frameworks, scripts, and utilities to automate data engineering processes.
Participate in DevOps practices, including CI/CD pipelines, code reviews, testing, and deployment automation.
Maintain technical documentation, design specifications, and operational procedures.
Contribute to platform enhancements and continuous improvement initiatives.
Apply software engineering best practices, including version control, test automation, code quality standards, and secure coding principles.
Collaboration & Stakeholder Engagement
Work closely with architects, product managers, data scientists, analysts, and business stakeholders to understand requirements and deliver technical solutions.
Participate in Agile teams and contribute to sprint planning, estimation, and delivery activities.
Provide technical guidance and knowledge sharing to team members and partners.
Participate in solution architecture reviews and contribute to technology roadmaps and design decisions.

Experience And Skill Set Requirements

Technical (Power BI) – 80%
Demonstrated technical experience in developing and supporting data engineering solutions.
Experience developing data solutions using Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Databricks, Delta Lake, and Lakehouse architecture principles.
Strong proficiency in Python, SQL, and Spark-based data processing frameworks.
Experience designing, developing, and maintaining scalable batch and near real-time data pipelines.
Experience developing data ingestion frameworks to onboard data from multiple source systems into enterprise data platforms.
Experience building and optimizing ETL/ELT processes for data transformation, cleansing, and preparation for analytics and reporting.
Experience developing and maintaining Databricks notebooks, workflows, and data processing jobs.
Experience implementing Spark-based data transformation pipelines and Databricks Lakehouse architecture.
Knowledge of medallion architecture patterns, including Bronze, Silver, and Gold layers.
Experience developing and managing Delta Lake tables and optimizing data processing workloads for performance and scalability.
Experience designing and managing data solutions using Azure Data Lake Storage (ADLS).
Experience implementing data partitioning, optimization, and archival strategies.
Knowledge of metadata management, data cataloguing, and data governance practices.
Experience implementing data validation, monitoring, and reconciliation processes to ensure data quality and reliability.
Experience working with Azure DevOps, Git, CI/CD pipelines, and automated deployment practices.
Experience developing reusable frameworks, scripts, and utilities to automate data engineering processes.
Experience with REST APIs, application integration patterns, and automation frameworks.
Knowledge of data governance, security, privacy, and access control principles.
Understanding of software engineering best practices, including version control, test automation, code quality standards, and secure coding principles.
Ability to maintain technical documentation, design specifications, and operational procedures.
Ability to contribute to platform enhancements and continuous improvement initiatives.
Communication – 10%
Strong verbal and written communication skills.
Ability to work effectively with architects, product managers, data scientists, analysts, and business stakeholders.
Ability to understand business and technical requirements and translate them into effective technical solutions.
Ability to participate in Agile teams, sprint planning, estimation, and delivery activities.
Ability to provide technical guidance and knowledge sharing to team members and partners.
Ability to participate in solution architecture reviews and contribute to technology roadmaps and design decisions.
Strong collaboration and stakeholder engagement skills.
Public Sector Experience – 10%
Experience working in public sector environments.
Understanding of government enterprise technology environments and data-driven decision-making initiatives.
Ability to work with government ministries, organizations, and stakeholders.
Understanding of data governance, security, privacy, and access control requirements in public sector environments.
Ability to contribute to enterprise data platform initiatives and deliver high-quality data solutions across government organizations.

How to Apply

If you are interested and your profile matches the requirements, kindly send the following mandatory documents to hrsmss@smsoftconsulting.com by Tuesday, November 10, 2026, at 10:00 AM EST.

Mandatory Documents

Updated Resume in Word format (Mandatory)
References (Mandatory)
Expected Hourly Rate (Mandatory)
Visa Status (Mandatory)
LinkedIn ID (Mandatory)

Without the mandatory documents, we cannot submit a candidate.

WhatsApp Group

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Additional Information

Onsite Requirement: 5 days per week.

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

Develop and maintain scalable data pipelines, ingestion frameworks, and ETL/ELT processes using Azure Data Factory, Databricks, Azure Data Lake Storage, Spark, and Delta Lake. Support data quality, governance, security, deployment automation, platform operations, and collaboration with technical and business stakeholders on Ontario Data Platform solutions.

Requirements

A degree or diploma in Computer Science, Software Engineering, Information Technology, or a related field is required, along with proficiency in Python, SQL, and Spark-based processing. Candidates should have experience with Azure data technologies, CI/CD and version control, data integration and governance, and strong communication and collaboration skills.

Skills

Azure Data Factory
Azure Data Lake Storage
Databricks
Delta Lake
Lakehouse Architecture
Python
SQL
Apache Spark
ETL/ELT
Data Pipeline Development
Azure DevOps
Git
CI/CD
REST APIs
Data Governance
Data Quality

Visa sponsorship

Not detected in the job text

Keywords

Azure Data Factory
Azure Data Lake Storage
Databricks
Delta Lake
Lakehouse Architecture
Python
SQL
Apache Spark
ETL/ELT
Data Pipelines
Data Ingestion
Medallion Architecture
Bronze, Silver, And Gold Layers
Azure DevOps
Git
CI/CD
REST APIs
Data Governance
Data Security
Data Privacy
Access Control
Data Quality
Metadata Management
Data Cataloguing
Agile
Automation
Ontario Data Platform
Public Sector
Data Engineering
Enterprise Data Solutions

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