Data Analyst

Data Engineering:

• Design, develop, and maintain scalable data pipelines to ingest, transform, and store large volumes of data both on-premises (SSIS etc.) and in the cloud (Azure, AWS, GCP)
• Ensure data integrity, accuracy, and availability for analytical and operational use.
• Collaborate with software engineers, data scientists, and business stakeholders to understand data requirements and implement solutions.
• Optimize and improve existing data workflows and ETL processes.
• Implement data governance and security best practices.
• Manage data storage solutions, such as data lakes and data warehouses.
• A successful history of manipulating, processing and extracting value from large, disconnected datasets.
• Deploy data solutions in the cloud and with database tools (SQL, NoSQL).

Data Analytics:

• Perform exploratory data analysis to identify trends, patterns, and insights.
• Develop and maintain reports, dashboards, and visualizations using BI tools (e.g., Power BI, SaaS VA).
• Conduct statistical analysis and modeling to support business strategies.
• Communicate findings and recommendations to stakeholders in a clear and concise manner.
• Use SQL and other query languages to extract and manipulate data from various sources.
• Create plans and strategies to integrate data models and improve service delivery.
• Develop and share service metrics and performance dashboards.
• Facilitate the frequent delivery of services and deliverables to ensure the successful creation of the target state while mentoring Agile Teams to grow their analytics fluency.
• Support corporate priorities with data-driven evidence using analytics, visualizations, and data modeling.
• The Province and the Contractor shall determine changes to Services and Materials as required. The Province and the Contractor will determine changes to Services and Materials through the Artifacts