Data Analyst - Remote - SDAB

Job Title: Data Analyst / Data Product Analyst Location: Edmonton, AB (Remote within Canada) Job Type: Contract Duration: 9 Months Pay Rate: CAD $38–$48 per hour Note: This job doesn't offer any benefits. Position Overview We are seeking a Data Product Analyst to develop and maintain data pipelines, integrate data sources, and deliver reliable, analytics-ready datasets using Microsoft Azure technologies. Required Qualifications • Post-secondary degree, diploma, or certificate in Computer Science or a related field. • 3 years of experience building data pipelines using Azure Databricks, Delta Lake, Workflows, Jobs, and Notebooks. • 3 years of experience designing analytics-ready datasets, semantic layers, data marts, and data products. • 2 years of experience in data governance, security, and metadata management. • 4 years of experience using GitHub/Git for version control and collaborative development. • 3 years of experience with Azure services, including Storage, SQL, Synapse, networking, and secure authentication. • 5 years of experience with Python, PySpark, and SQL for enterprise ETL/ELT workflows. • 1 year of experience using AI for code generation, data analysis, automation, or data engineering. Preferred Qualifications • 6 years of experience in business requirements analysis, data transformation, cleansing, and data wrangling. • 6 years of experience with Microsoft SQL Server, including database design and optimization. • Experience with Azure Synapse Analytics and Microsoft Fabric. • Experience developing data products in a Government of Alberta cloud environment. • Experience with Talend, REST APIs, ServiceNow integrations, and Azure Data Management Platforms. • Experience with message queuing technologies such as ActiveMQ and Azure Service Bus. • Experience collaborating with cross-functional teams to develop data products and software applications. Responsibilities • Design and maintain scalable data pipelines using Azure Data Factory, Azure Databricks, and Azure Synapse Analytics. • Integrate data from multiple systems, including ServiceNow and geospatial platforms. • Develop data models, semantic layers, and analytics-ready datasets. • Use Python and SQL for data transformation, cleansing, and optimization. • Implement data governance, metadata management, data quality, and security controls. • Develop secure APIs and data integrations for downstream systems. • Monitor and troubleshoot data pipelines to ensure reliability and performance. • Use AI-assisted tools to improve code development, testing, and automation. • Collaborate with technical teams and stakeholders to deliver data solutions supporting analytics and regulatory decision-making.