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Bi Data Engineer (6-Month Contract)
Company | OMERS |
Address | Toronto, Ontario, Canada |
Employment type | FULL_TIME |
Salary | |
Category | Financial Services |
Expires | 2023-09-20 |
Posted at | 9 months ago |
We are looking for a BI Data Engineer with Azure Data Engineering experience to join our team. As a key member of the Enterprise Data and Advanced Analytics team, this role is instrumental in enhancing data & analytics capabilities by championing industry best practices and delivering high quality reports and training to enhance business decision making. They help translate complex solutions to digestible business-centric outcomes and will do so by building interactive data visualizations using Power BI and sophisticated data models.
- Deploying ETL pipelines to achieve a high level of reliability, scalability, and security.
- Designing and building interactive insightful data products using Power BI, ML and Azure
- Identifying, defining, and implementing opportunities for enhancing existing processes
- The ideal candidate will have the ability to document technical specifications, workflows, and guidelines, ensuring clear and concise communication across the team and stakeholders
- The candidate should have experience in creating dataflows using Azure Data Factory and familiarity with the Medallion Architecture is highly desirable
- The ideal candidate will possess strong communication and leadership skills to guide and support the team in adopting and implementing industry-leading data engineering practices
- Knowledge of Postman, the candidate should be able to effectively design, test, and debug APIs, ensuring their functionality and reliability within our software ecosystem
- Designing and developing ETL pipelines to achieve a high level of reliability, scalability, and security. Sourcing, transforming, and delivering structured and unstructured assets for use in Azure Synapse Analytics, Azure Data Factory, SQL Server, Azure Data Lake
- Leading multiple projects simultaneously and ensuring on-time delivery
- Operating in an Agile development environment
- The candidate should be well-versed in the concepts and techniques of the Kimball Methodology, which emphasizes building data warehouses that are optimized for business intelligence and reporting. Proficiency in dimensional modeling, including the creation of star schemas and snowflake schemas, is essential
- Defining and implementing technical test plans and perform unit and integration testing
- The candidate should have a strong command of Pyspark, a Python library for distributed data processing and analysis
- Developing and monitoring Azure data pipelines, Power BI Premium Dataflows to gather, transform and democratize structured and unstructured data assets
- Managing change and communicating impacts to stakeholders and fellow team members
- SQL Server Data Tools
- Problem-Solving. Must be able to trace data lineage / workflows and resolve technical issues with minimal supervision. Demonstrated proficiency in understanding and implementing business workflows is a plus.
- Industry Knowledge. The ability to quickly propose Azure Data Platform solutions by recalling the latest standard processes learned from MVP & Product Team articles, MSFT documentation, whitepapers, and community publications is required
- Azure Synapse & Azure Data Factory
- Azure Machine Learning
- Experience. 5+ years solving sophisticated technical data projects using the Microsoft Azure data stack is required
- Teamwork. Motivated and keen to work in a collaborative environment with a focus on team success over and above individual success.
- Azure Databricks using PySpark
- Relationship Building. A proven track record of building deep technical relationships. Experience in setting expectations across various partners.
- Breadth of technical experience and knowledge across the Azure Data Platform, with depth Domain Expertise in two or more of the following Data Platform resources is required
- Excellent written, verbal, and presentation skills targeted at all levels of the organization
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