Senior Data Engineer –

- GOAPRDJP00000991

Job Overview

We are seeking a Senior Data Engineer / Data Product Analyst for the Government of Alberta to support data modernization initiatives and the Digital Regulatory Assurance System (DRAS) program.

This role will focus on designing, developing, operating, and continuously improving reliable data products and platform solutions. The successful candidate will build scalable Azure-based data pipelines, trusted analytics-ready datasets, data models, semantic layers, and integrations that support regulatory oversight, compliance monitoring, reporting, advanced analytics, and future AI use cases.

The position also provides operational support and continuous improvement services to ensure the reliability, availability, scalability, and performance of DRAS data assets, integrations, reports, and analytics products.

Role Snapshot

Position Details Information Job Title GOAPRDJP00000991 –

- Data Engineer –
- Senior Client Government of Alberta Work Location 9942 – 108 ST, Edmonton, Alberta, Canada, T5K 2J5 Work Arrangement Remote Estimated Start Date January 9, 2026 Estimated End Date August 31, 2027 Estimated Hours/Day 7.25 Maximum Extension 6 Months Application Deadline Monday, August 17, 2026 at 4:00 PM EST

Key Responsibilities

- Data Product Development &
- Architecture
- Collaborate with business stakeholders and product owners to understand data product objectives, requirements, and success criteria.
- Design and implement scalable, secure, and high-performance data architectures on Microsoft Azure.
- Support both cloud-native and hybrid data environments.
- Design, build, and operate reliable data pipelines that ingest and integrate data into the Data Management Platform.
- Develop standardized, trusted, analytics-ready datasets for reporting, self-service analytics, data science, and advanced analytics.
- Design and curate high-quality datasets suitable for future AI use cases.
- Data Engineering &
- Pipeline Development
- Lead the development of data ingestion, transformation, and integration pipelines using:
- Azure Data Factory
- Azure Databricks
- Azure Synapse Analytics
- Build and optimize enterprise-grade ETL/ELT workflows using Python, PySpark, and SQL.
- Develop scalable pipelines using Delta Lake, Databricks Workflows, Jobs, and Notebooks.
- Perform cluster management and optimize data processing workloads.
- Apply data cleansing, enrichment, transformation, and quality controls.
- Monitor and troubleshoot pipelines to ensure reliability, scalability, and performance.
- Data Lake, Modeling &
- Analytics
- Work with the Data Architect to manage data lakes and structured storage solutions using Azure Data Lake Storage Gen2.
- Ensure efficient, secure, governed access to data assets.
- Develop and maintain robust data models and semantic layers.
- Design data marts and data products supporting operational reporting, analytics, machine learning, and downstream consumption.
- Support integration and extension of data solutions with Azure Synapse Analytics and Microsoft Fabric.
- Enable self-service reporting, data science, and enterprise analytics capabilities.
- Data Integration &
- APIs
- Integrate data from diverse source systems, including ServiceNow and geospatial systems.
- Utilize APIs, connectors, and custom scripts to support enterprise data integration.




- Design and expose secure data services and APIs using Azure API Management.
- Develop secure and scalable RESTful APIs for data exchange and automation.
- Support real-time and asynchronous data integration where required.
- Data Governance, Security &
- Compliance
- Implement data governance practices including:
- Metadata management
- Data classification
- Data lineage
- Data quality

- Ensure compliance with privacy and regulatory standards, including FOIP and GDPR.
- Implement role-based access controls, encryption, and data masking.
- Utilize secure Azure authentication mechanisms such as Service Principals and Managed Identities.
- Ensure data solutions meet enterprise security, governance, and compliance requirements.
- Operational Support &
- Continuous Improvement
- Provide operational support and continuous improvement for DRAS data products and platform solutions.
- Monitor the availability, reliability, scalability, and performance of data assets, integrations, reports, and analytics products.
- Troubleshoot data pipelines and integrations and resolve performance or reliability issues.
- Identify opportunities for continuous improvement and optimization across data engineering workflows.
- Maintain stable and reliable production data services.
- AI, Automation &
- Development Productivity
- Utilize AI and automation tools to streamline data engineering workflows, including:

- Pipeline development
- Testing
- Monitoring
- Documentation
- Data analysis

- Leverage AI-assisted tools for code generation, optimization, and code review.
- Identify opportunities to improve development efficiency, productivity, and code quality through AI-enabled solutions.
- Collaboration &
- Stakeholder Engagement
- Work closely with business stakeholders, product owners, Data Architects, engineers, and other cross-functional teams.
- Translate business requirements into scalable technical data solutions.
- Collaborate with teams to create software applications and data products.
- Support additional enterprise data initiatives as required.

Required Skills & Experience –

- Must Have

- Experience designing data solutions for analytics-ready, trusted datasets using tools such as Power BI and Azure Synapse.
- Experience developing semantic layers, data marts, and data products for self-service analytics, data science, reporting, and downstream consumption.
- Solid experience with Git/GitHub for version control, collaborative development, code management, and data engineering workflows.
- Strong experience with Azure services, including Storage, SQL, Synapse, and networking.
- Experience implementing secure authentication using Service Principals and Managed Identities.
- Strong programming experience with Python, PySpark, and SQL.
- Experience developing, orchestrating, and optimizing enterprise-grade ETL/ELT workflows in large-scale cloud environments.
- Hands-on experience building scalable data pipelines using Azure Databricks, Delta Lake, Workflows, Jobs, and Notebooks.




- Experience with Databricks cluster management.
- Experience using AI for code generation, data analysis, automation, and productivity enhancement within data engineering workflows.

Nice-to-Have Skills
- Direct hands-on experience performing business requirements analysis related to data manipulation, transformation, cleansing, and wrangling.
- Strong technical knowledge of Microsoft SQL Server, including database design, optimization, and administration.
- Experience extending or integrating data solutions with Azure Synapse Analytics and Microsoft Fabric, including:
- Lakehouse
- Warehouse
- Semantic Models

- Direct experience building data products within the Government of Alberta cloud environment.
- Experience building secure and scalable RESTful APIs for data exchange, including authentication, error handling, and real-time automation.
- Experience with Message Queueing Technologies, including ActiveMQ and Azure Service Bus.
- Experience implementing scalable, asynchronous communication across distributed systems.
- Experience working with cross-functional teams to create software applications and data products.

Project &
- Business Context The Government of Alberta is undertaking modernization initiatives that are transforming how ministry users collect, manage, analyze, and consume data as legacy systems transition to modern Data Management and Geospatial Platforms.

The Digital Regulatory Assurance System (DRAS) is a Government of Alberta regulatory transformation initiative led by Environment and Protected Areas (EPA). DRAS is designed to modernize, digitize, and streamline environmental and natural resource regulatory processes across the complete regulatory lifecycle, from application and authorization through monitoring, compliance, remediation, and closure.

As DRAS development continues, the volume, variety, and complexity of structured data continue to grow. This creates an ongoing need for dedicated data engineering and data product expertise.

The Senior Data Engineer / Data Product Analyst will design, build, operate, and continuously improve reliable data products and platform solutions. The role will ensure that modernized data assets deliver tangible business value by producing trusted, analytics-ready datasets that support regulatory oversight, compliance monitoring, evidence-based decision-making, operational reporting, advanced analytics, and future AI initiatives.

Work Arrangement

Remote: The resource will primarily work remotely.

How to Apply

If you have the required experience and are available for new opportunities, please submit the following documents to [email protected] by Monday, August 17, 2026 at 4:00 PM EST:

- Updated Resume in Word format –
- Mandatory
- Skills Matrix and References –
- Mandatory
- Expected Hourly Rate –
- Mandatory
- Visa Status –
- Mandatory
- LinkedIn ID –
- Mandatory

Please note: Applications without the mandatory documents cannot be processed or submitted. Apply Online For daily job updates, you can also join our WhatsApp group.

If this opportunity is not a match for your profile, please share it with qualified Senior Data Engineers / Data Product Analysts with strong Azure, Databricks, Synapse, Python/PySpark, SQL, data architecture, data products, data governance, and AI-assisted engineering experience.

📌 GOAPR991 - Data Engineer - Senior (Edmonton)
🏢 S M Software Solutions
📍 Edmonton