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.