Job Summary:

The Junior Report Developer will support the design, development, and operation of scalable enterprise data solutions on the Ontario Data Platform. Utilizing modern cloud technologies such as Azure Data Factory, Databricks, and Azure Data Lake Storage, this role focuses on building and optimizing data pipelines, enabling analytics use cases, and delivering high-quality data products across government sectors.

Responsibilities:

- Design, develop, and maintain batch and near real-time data pipelines using Azure Data Factory and Databricks.
- Develop data ingestion frameworks to onboard data from diverse source systems.
- Build and optimize ETL/ELT processes for data transformation, cleansing, and preparation.
- Implement data validation, monitoring, and reconciliation to ensure data quality and reliability.
- Create and manage Databricks notebooks, workflows, and data processing jobs leveraging Spark and Lakehouse architecture.
- Manage data storage solutions using Azure Data Lake Storage and optimize data partitioning and archival strategies.
- Develop automation frameworks, scripts, and utilities to streamline data engineering processes.
- Participate in DevOps practices including CI/CD pipeline development, code reviews, and deployment automation.
- Collaborate with architects, product managers, data scientists, and business stakeholders to deliver technical solutions.
- Contribute to Agile team activities such as sprint planning, estimation, and delivery.
- Maintain technical documentation and support continuous platform improvements.

Required Skills:
- Degree or diploma in Computer Science, Software Engineering, Information Technology, or related field.
- Experience with Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), Databricks, and Delta Lake.
- Proficiency in Python, SQL,



and Spark-based data processing frameworks.
- Familiarity with Azure DevOps, Git, CI/CD pipelines, and automated deployment.
- Understanding of data governance, security, privacy, and access control principles.
- Experience with REST APIs and application integration patterns.

Desired Skills:
- Knowledge of medallion architecture patterns (Bronze, Silver, Gold) in data pipelines.
- Experience with data cataloguing and metadata management.
- Strong software engineering practices including version control, test automation, and secure coding.
- Ability to troubleshoot and optimize performance of Databricks jobs and data processing workloads.
- Experience working in Agile development environments.

Rated Criteria:
- Technical Proficiency with Azure Data Platform and Databricks - 50 Points
- Data Pipeline Development and Optimization Skills - 20 Points
- Communication and Collaboration Abilities - 10 Points
- Experience with DevOps and Automation Practices - 10 Points
- Public Sector Experience - 10 Points

Total: 100 Points Deliverables:
- Scalable and reliable data pipelines supporting batch and near real-time processing.
- Automated ETL/ELT workflows and data ingestion frameworks.
- Databricks notebooks and workflows optimized for performance and scalability.
- Technical documentation including design specifications and operational procedures.
- Continuous integration and deployment pipelines for data engineering solutions.

Must Haves:
- Proven experience with Azure Data Factory, Azure Data Lake Storage, and Databricks.
- Robust programming skills in Python, SQL, and Spark.
- Understanding of data governance and security best practices.
- Experience with CI/CD pipelines and version control systems.
- Degree or diploma in a relevant technical field.

Public Sector Experience:

Preferred

📌 Data Engineer (Ontario)
🏢 vTech Solution
📍 Ontario