Senior Data Engineer –

- GOAPRDJP00000982

Job Overview The Government of Alberta (GoA) is seeking a Senior Data Engineer to support digital transformation initiatives within the Digital Design and Delivery (DDD) division.

The successful candidate will work across multidisciplinary product teams to design, develop, and maintain contemporary data solutions, including scalable data pipelines, data integration and migration capabilities, enterprise data models, analytics, reporting, and data governance solutions.

This role requires a combination of strong data engineering, analytics, cloud/hybrid data platform, data modernization, and business intelligence expertise. The successful candidate will help ministries improve data quality and accessibility, strengthen self-service analytics, and enable informed decision-making supporting modern digital services.

Role Snapshot

Position Details Information Job Title GOAPRDJP00000982 –

- Data Engineer –
- Senior Client Government of Alberta Work Location 7000 – 113 ST, Edmonton, Alberta, Canada, T6H 5T6 Work Arrangement Remote Estimated Start Date September 14, 2026 Estimated End Date September 30, 2027 Estimated Hours/Day 7.25 Maximum Extension 24 Months Application Deadline Monday, August 17, 2026 at 4:00 PM EST

Key Responsibilities

- Data Engineering &
- Pipeline Development
- Design, build, maintain, and optimize scalable data pipelines across on-premises and cloud platforms, including Azure, Databricks, Microsoft Fabric, GCP, and AWS.
- Develop end-to-end ETL/ELT workflows to ingest, transform, validate, and store diverse datasets.
- Integrate data from relational databases, NoSQL platforms, APIs, and files.
- Apply data validation, error handling, logging, monitoring, and scheduling to ensure reliable data operations.
- Optimize ETL/ELT processes through automation, performance tuning, and scalability improvements.
- Support high-volume data processing and resolve pipeline bottlenecks.
- Develop reusable and reliable data integration solutions for enterprise business use cases.
- Data Modeling, Warehousing &
- Lakehouse
- Develop and maintain enterprise data models using Star and Snowflake schemas.
- Design fact and dimension models to improve query performance, scalability, and usability.
- Support enterprise data warehouse and lakehouse implementations.
- Prepare curated data marts, fact tables, and dimension tables for analytics and reporting.
- Support the management and governance of enterprise data platforms, including data lakes, data warehouses, security controls, and access management.
- Ensure data solutions are scalable, secure, governed, and optimized for analytics.
- Data Migration &
- Modernization
- Plan, execute, validate, and support data migrations across on-premises, cloud, and cross-database environments.
- Support cloud modernization and hybrid data platform implementations.
- Develop migration strategies and data validation processes to ensure accuracy and completeness.
- Modernize legacy data integration and processing workflows.
- Support enterprise data transformation initiatives across multiple projects.
- ETL/ELT &
- Cloud Data Technologies
- Develop and operate ETL/ELT workflows using technologies such as:
- SSIS
- Azure/Fabric Data Factory
- Dataflows
- Notebooks
- Azure
- Databricks
- Microsoft Fabric
- Apply Python, PySpark, and SQL to develop, orchestrate, optimize, and maintain enterprise-grade data workflows.
- Utilize modern lakehouse and big-data technologies such as Spark and Delta Lake.
- Support cloud and hybrid data environments across multiple technology platforms.
- Data Integration &
- AI-Enabled Data Engineering
- Integrate data from diverse enterprise sources and platforms.
- Apply AI-enabled data integration techniques, including:
- Intelligent data mapping




- Schema discovery
- Metadata enrichment
- Automated data quality validation

- Use AI-assisted development tools to improve productivity, code quality, documentation, testing, and data engineering workflows.
- Apply appropriate review and quality controls to AI-assisted development.
- Business Intelligence &
- Data Analytics
- Analyze datasets to identify trends, patterns, anomalies, and actionable insights.
- Develop executive dashboards, KPI reporting, self-service BI solutions, and business performance reporting.
- Develop interactive Power BI dashboards and reports using DAX.
- Create calculated columns and measures to monitor KPIs and support service-level reporting.
- Develop predictive and descriptive models using statistical methods, Python, or R-based machine learning techniques.
- Design and integrate data models that support improved service delivery.
- Provide data-driven analysis, visualizations, and AI-enabled insights supporting corporate priorities and strategic initiatives.
- CI/CD, DevOps &
- Data Platform Operations
- Automate data pipeline deployment and operations using CI/CD practices.
- Implement automated testing, release management, monitoring, and deployment processes.
- Support DevOps and Infrastructure as Code practices for cloud-based data platforms and services.
- Improve reliability, scalability, and speed of data solution delivery through automation.
- Support security, access management, governance, and operational controls across enterprise data platforms.
- Stakeholder Collaboration &
- Agile Delivery
- Work closely with architects, developers, business stakeholders, product teams, and other technical professionals.
- Translate business and technical requirements into scalable data solutions.
- Deliver analytics and data engineering solutions iteratively within an Agile environment.
- Present complex data findings to non-technical audiences in clear, actionable terms.
- Provide recommendations based on data analysis to support informed decision-making.
- Mentor teams and promote analytics fluency and self-service data capabilities.
- Work across two to three projects based on project requirements and priorities.

Required Skills & Experience –

- Must Have

- Bachelor's degree in Computer Science, Information Technology, Engineering, Mathematics, Statistics, Data Science, or a related field.
- Experience as a Data Engineer and/or Data Analyst.
- Strong experience in Business Intelligence and Executive Reporting, including executive dashboards, KPI reporting, self-service BI, and business performance reporting.
- Experience with cloud or hybrid data platforms and cloud modernization initiatives.
- Experience planning, executing, validating, and supporting data migrations across on-premises, cloud, and cross-database environments.
- Experience with enterprise data warehouse or lakehouse design, including Star/Snowflake schemas and fact/dimension modeling.
- Strong experience with Python, PySpark, and SQL for enterprise-grade ETL/ELT workflows.
- Knowledge of ETL processes and tools, with hands-on experience designing and implementing data pipelines that transform and load data from multiple sources into data warehouses.
- Experience with data integration, analytics, reporting, and enterprise data platforms.
- Strong understanding of data quality, data governance, and secure data platform practices.

Nice-to-Have Skills




- Experience using AI-assisted development tools and practices to improve productivity, code quality, documentation, testing, and data engineering workflows.
- Experience with DevOps, CI/CD, and Infrastructure as Code for automated deployment, configuration, and management of cloud-based data platforms.
- Experience with modern data technologies including:
- Microsoft Fabric
- Databricks
- Apache Spark
- Delta Lake
- Other modern lakehouse/big-data platforms

- Experience supporting enterprise-scale public service applications in public-sector or mixed-delivery environments.
- Experience with DAX, Python, and R for advanced analytics and business intelligence.
- Experience developing predictive or descriptive models using statistical and machine learning techniques.
- Experience working with cloud platforms including Azure, GCP, and AWS.

Project &
- Business Context The Government of Alberta is transforming how government services are designed and delivered to provide simpler, more efficient, and better services for Albertans.

The Digital Design and Delivery (DDD) division serves as the Government of Alberta's center for modern digital delivery. DDD partners with ministries to design and deliver digital products, platforms, and services using human-centered design, Agile delivery, modern data practices, and AI-enabled approaches.

Working within multidisciplinary product teams, Senior Data Engineers will collaborate with business and technical stakeholders to understand data requirements and develop modern data solutions.

The role supports the delivery of data pipelines, integration and migration capabilities, data models, analytics, reporting, and data governance practices. By combining technical data engineering expertise with analytical capabilities, the successful candidate will help ministries improve data quality and accessibility, strengthen self-service analytics, and make informed decisions that support modern digital services across the Government of Alberta.

Scope of Services

- The Senior Data Engineer will work on a full-time basis across approximately two to three projects.
- Time, location, and frequency of work may vary depending on project requirements.
- The resource may work a maximum of approximately 1,960 hours per term, unless otherwise agreed upon with the Province.
- Hours may vary depending on the nature and requirements of assigned projects.
- Services and deliverables will evolve iteratively in response to emerging user and business needs and changing technical opportunities.
- The resource will contribute to data engineering, analytics, modernization, migration, integration, reporting, governance, and continuous improvement initiatives.

Work Arrangement Remote: The Data Engineer will work remotely.

However, the resource may be required to attend meetings or work sessions in Edmonton with reasonable notice from the Province.

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 Analysts with strong experience in cloud data platforms, ETL/ELT, Python/PySpark, SQL, data migration, data warehousing/lakehouse, Power BI, analytics, and modern data engineering technologies.

📌 GOAPR982 - Data Engineer - Senior (Edmonton)
🏢 S M Software Solutions
📍 Edmonton