RQ11673 Report Developer Junior
Maarut
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.
Requirements
Experience and Skill Set Requirements:
Must Haves:
- 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.
Skill Set Requirements:
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.
Evaluation breakdown:
- Technical(Power BI)
- Communication
- Public Sector exp
Required Skills:
Experience and Skill Set Requirements: Must Haves: 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. Skill Set Requirements: 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. Evaluation breakdown: Technical(Power BI) Communication Public Sector exp
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