Role overview

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.