Backend developer • toronto on
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Report Developer Junior
Location: Toronto, Ontario
Employment Type: Contract
Work Arrangement: 5 Days Onsite
Hourly Rate: CAD $40 - 45 Inc
Contract Duration: 133 + 133 Days
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 Report Developer Junior 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.
Qualifications and Technical Requirements
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.
Experience with Power BI.
Key Responsibilities 1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
Candidate Evaluation Criteria 1. Technical Skills
Experience with Power BI.
Experience with Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Databricks, and Delta Lake.
Understanding of Lakehouse architecture principles.
Proficiency in Python, SQL, and Spark-based data processing frameworks.
Experience developing and maintaining data pipelines and ETL/ELT processes.
Experience with Databricks notebooks, workflows, and Medallion Architecture.
Experience with Azure DevOps, Git, CI/CD pipelines, and automated deployment practices.
Knowledge of data governance, security, privacy, and access control.
Experience with REST APIs, application integration patterns, and automation frameworks.
2. Communication
Ability to communicate effectively with architects, product managers, data scientists, analysts, and business stakeholders.
Ability to participate in Agile teams, sprint planning, estimation, and delivery activities.
Ability to provide technical guidance and knowledge sharing.
3. Public Sector Experience
Experience working with public sector organizations.
Understanding of government data environments and initiatives.
