Data Analyst (Remote) JP927

Pathlion; Edmonton; Remote; CAD 80,000 - 115,000; Full time

Job summary

Pathlion is seeking a Data Product Analyst to support the Digital Regulatory Assurance System (DRAS) program in Edmonton, Canada. This role focuses on developing, managing, and optimizing data architectures on Microsoft Azure.

The Data Product Analyst will lead data ingestion and transformation processes, ensuring compliance with regulatory standards while integrating data from diverse systems. Proficiency in Azure technologies is essential for success in this position.

Qualifications

• Strong experience designing and implementing data architectures on Azure.
• Ability to develop and manage data ingestion and transformation processes.
• Proven expertise in data governance and ensuring regulatory compliance.

Responsibilities

• Design and implement secure and high-performance data architecture on Microsoft Azure.
• Lead development of data pipelines using Azure services.
• Integrate data from various source systems using APIs and custom scripts.

Skills

Data architecture design

Data ingestion pipelines

Azure Data Factory

Python

SQL

Data governance

AI tools for data engineering

Tools

Azure Databricks

Azure Synapse Analytics

Azure API Management

Azure Data Lake Storage Gen2

Job description

Project Name

Digital Regulatory Assurance System

Job Title

Data Product Analyst

Scope

The Data Product Analyst – Intermediate will primarily support the Digital Regulatory Assurance System (DRAS) program, where high quality, timely analytics are essential to regulatory and compliance functions. As data and analytics maturity increases, the role may be expanded to support additional enterprise data initiatives. Modernization initiatives across the Government of Alberta are fundamentally changing how ministry users collect, manage, analyze, and use data as legacy systems are transformed into modern Data Management and Geospatial Platforms. This shift requires dedicated analytical capacity to ensure that the value of modernized data assets is fully realized. DRAS is a Government of Alberta regulatory transformation initiative led by Environment and Protected Areas (EPA) to modernize, digitize, and streamline environmental and natural resource regulatory processes. DRAS supports the full regulatory lifecycle, from application and authorization to monitoring, compliance monitoring, remediation, and closure through a single, consolidated digital platform. As DRAS development continues, the volume, variety, and complexity of structured data continue to grow, creating a sustained need for dedicated data engineering and data product expertise. The Data Product Analyst role is critical to ensuring that modernization delivers tangible business value. This role will design, build, and operate reliable data pipelines that ingest and integrate data into the DMP, apply standardized transformations, enforce data quality and governance controls, and produce trusted, analytics‑ready datasets that support regulatory oversight, compliance monitoring, and evidence‑based decision‑making aligned with DRAS objectives.

Duties

• Design and implement scalable, secure, and high-performance data architecture on Microsoft Azure, supporting both cloud‑native and hybrid environments.
• Lead the development of data ingestion, transformation, and integration pipelines using Azure Data Factory, Azure Databricks, and Azure Synapse Analytics.
• Work with the Data Architect and manage data lakes and structured storage solutions using Azure Data Lake Storage Gen2, ensuring efficient access and governance.
• Integrate data from diverse source systems including ServiceNow, and geospatial systems, using APIs, connectors, and custom scripts.
• Develop and maintain robust data models and semantic layers to support operational reporting, analytics, and machine learning use cases.
• Build and optimize data workflows using Python and SQL for data cleansing, enrichment, and advanced analytics within Azure Databricks.
• Design and expose secure data services and APIs using Azure API Management for downstream systems.
• Implement data governance practices, including metadata management, data classification, and lineage tracking.
• Ensure compliance with privacy and regulatory standards (e.g., FOIP, GDPR) through role‑based access controls, encryption, and data masking.
• Monitor and troubleshoot data pipelines and integrations, ensuring reliability, scalability, and performance across the platform.
• Utilize AI and automation tools to streamline data engineering workflows, including pipeline development, testing, monitoring, and documentation.
• Leverage AI‑assisted tools for code generation, optimization, and review to improve development efficiency and code quality.
• Design and curate standardized, high‑quality datasets that are suitable for advanced analytics and future AI use cases.