Report Developer / Azure Data Engineer
- Toronto, ON, Canada
Contract
Applications open in a new tab.
Job details
- Job type
- Contract
- Apply by
- Posting language
- English
- Posted
Original job description
Our Client is seeking a Report Developer / Azure Data Engineer to support enterprise data engineering, cloud integration, and analytics initiatives within the Ontario Data Platform (ODP).
The successful candidate will develop scalable data pipelines, optimize data processing workflows, and support enterprise analytics solutions using Microsoft Azure, Databricks, Python, SQL, and Spark.
Key Responsibilities
The successful candidate will develop scalable data pipelines, optimize data processing workflows, and support enterprise analytics solutions using Microsoft Azure, Databricks, Python, SQL, and Spark.
Key Responsibilities
- Design, develop, and maintain batch and near real-time data pipelines using Azure Data Factory (ADF), Databricks, and Azure Data Lake Storage (ADLS).
- Build and optimize ETL/ELT processes for data ingestion, transformation, cleansing, and integration.
- Develop Databricks notebooks, workflows, and Spark-based data processing jobs.
- Implement Delta Lake and Lakehouse architecture, including Bronze, Silver, and Gold data layers.
- Create and maintain reliable data validation, reconciliation, monitoring, and quality-control processes.
- Optimize data storage, partitioning, and processing performance.
- Support data governance, metadata management, security, and access-control practices.
- Develop reusable Python scripts, automation utilities, and integration frameworks.
- Implement CI/CD pipelines, version control, automated testing, and deployment processes using Azure DevOps and Git.
- Collaborate with architects, analysts, developers, and business stakeholders to deliver enterprise data solutions.
- Support reporting, analytics, technical documentation, and Agile development activities.
- Hands-on experience with Azure Data Factory (ADF), Azure Data Lake Storage (ADLS), and Azure Databricks.
- Strong proficiency in Python, SQL, Apache Spark, and PySpark.
- Experience with Delta Lake, Databricks Lakehouse, and Medallion Architecture.
- Knowledge of ETL/ELT development, data integration, and pipeline optimization.
- Experience with Azure DevOps, Git, CI/CD, and automated deployment.
- Understanding of data governance, data quality, privacy, and security principles.
- Experience working with REST APIs and enterprise integration patterns.
- Familiarity with Power BI and enterprise reporting environments.
- Strong communication, troubleshooting, and stakeholder collaboration skills.
- Public sector experience is an asset.
- Degree or diploma in Computer Science, Information Technology, Software Engineering, or a related discipline.
More about this job
Responsibilities
Design, develop, and optimize batch and near-real-time data pipelines, ETL/ELT workflows, and Spark-based processing using Azure, Databricks, Python, and SQL. Maintain data quality, governance, security, and deployment practices while collaborating with technical and business stakeholders on enterprise analytics and reporting solutions.
Requirements
Requires hands-on experience with Azure Data Factory, Azure Data Lake Storage, and Azure Databricks, along with strong Python, SQL, Spark, and PySpark skills. Candidates should also have experience with Delta Lake, CI/CD and Azure DevOps, data governance and quality, REST APIs, and enterprise reporting; a related degree or diploma is specified.
Skills
- Azure Data Factory
- Azure Data Lake Storage
- Azure Databricks
- Python
- SQL
- Apache Spark
- PySpark
- Delta Lake
- ETL/ELT
- Data Pipeline Development
- Azure DevOps
- Git
- CI/CD
- Data Governance
- REST APIs
- Power BI
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Government & Public Sector
Keywords
- Azure Data Factory
- Azure Data Lake Storage
- Azure Databricks
- Python
- SQL
- Apache Spark
- PySpark
- Delta Lake
- Lakehouse Architecture
- Medallion Architecture
- ETL/ELT
- Data Pipelines
- Data Integration
- Data Validation
- Data Quality
- Data Governance
- Metadata Management
- Data Security
- REST APIs
- Azure DevOps
- Git
- CI/CD
- Automated Testing
- Power BI
- Enterprise Reporting
- Agile Development
- Ontario Data Platform