Role overview:The Government of Alberta (GoA) has embarked on transforming the work of government to deliver simpler, more efficient, and better services for the citizens of Alberta, thereby ensuring that the needs of Albertans are effectively met in the digital age. The Province has a strategic role within government to drive efficiencies, innovation and modernization. The Digital Design and Delivery Division (DDD) is the Province’s new centre for digital delivery. It was established to maximize capability and confidence in modern digital practice by ensuring service quality and value through standards and controls. This includes utilizing human-centred design approaches together with agile methodology and modern data practices.
DDD is currently working with Ministries across the GoA, establishing working relationships with partner Ministries throughout this engagement.
Must Haves: - Bachelor degree in Computer Science, IT or related field of study.
- 3 years experience ensuring data quality, security, and governance.
- 5 years Experience as a Data Engineer and/or Data Analyst.
- 3 years Experience designing efficient dimensional models (star and snowflake schemas) for warehousing and analytics.
- 3 years Experience developing and maintaining reports, dashboards, and visualizations using Power BI, DAX, Tableau, or Python libraries.
- 5 years Experience manipulating and extracting data from diverse on-premises and cloud-based sources.
- 3 years Experience performing migrations across on-premises, cloud, and cross-database environments.
- 2 years Experience using Git, collaborative workflows, CI/CD pipelines, containerization (Docker/Kubernetes), and Infrastructure as Code (Terraform, ARM, CloudFormation) to deploy and migrate data solutions.
- 3 years Experience with SSIS, Azure Data Factory (ADF), and using APIs for extracting and integrating data across multiple platforms and applications.
Nice to Haves: - 2 years Experience in application development, with knowledge of object-oriented and functional programming/scripting languages.
- 1 years Experience in the Government of Alberta environment or an environment of equivalent size and complexity.
- 2 years Experience with databases and data integration, including PostgreSQL, MongoDB, Azure Cosmos DB and data intefration tools like Synapse pipeline, Fabric data factory, Informatica, Talend, DBT and Airbyte.
- 1 years Exposure to AI/ML tools and workflows relevant to data engineering, such as integrating AI-driven analytics or automation within cloud platforms like Databricks and Azure.
Responsibilities: • Design, build, and maintain data pipelines on-premises and in the cloud (Azure, GCP, AWS) to ingest, transform, and store large datasets. Ensure pipelines are reliable and support multiple business use cases.
• Create and optimize dimensional models (star/snowflake) to improve query performance and reporting. Ensure models are consistent, scalable, and easy for analysts to use.
• Integrate data from SQL, NoSQL, APIs, and files while maintaining accuracy and completeness. Apply validation checks and monitoring to ensure high-quality data.
• Improve ETL/ELT processes for efficiency and scalability. Redesign workflows to remove bottlenecks and handle large, disconnected datasets.
• Build and maintain end-to-end ETL/ELT pipelines with SSIS and Azure Data Factory. Implement error handling, logging, and scheduling for dependable operations.
• Automate deployment, testing, and monitoring of ETL workflows through CI/CD pipelines. Integrate releases into regular deployment cycles for faster, safer updates.
• Manage data lakes and warehouses with proper governance. Apply security best practices, including access controls and encryption.
• Partner with engineers, analysts, and stakeholders to translate requirements into solutions. Prepare curated data marts and fact/dimension tables to support self-service analytics.
Data Analytics:
• Analyze datasets to identify trends, patterns, and anomalies. Use statistical methods, DAX, Python, and R to generate insights that inform business strategies.
• Develop interactive dashboards and reports in Power BI using DAX for calculated columns and measures. Track key performance metrics, share service dashboards, and present results effectively.
• Build predictive or descriptive models using statistical, Python, or R-based machine learning methods. Design and integrate data models to improve service delivery.
• Present findings to non-technical audiences in clear, actionable terms. Translate complex data into business-focused insights and recommendations.
• Deliver analytics solutions iteratively in an Agile environment. Mentor teams to enhance analytics fluency and support self-service capabilities.
• Provide data-driven evidence to guide corporate priorities. Ensure strategies and initiatives are backed by strong analysis, visualizations, and models.
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