Senior Data Engineer building Dandy’s data infrastructure for its technology - powered dental operating system. Developing pipelines, governed data products, and AI - ready platform capabilities.
About the role
- Senior Data Engineer building cloud and on-premises data pipelines for Alberta government services. Developing Power BI analytics, data models, governance, and AI-enabled insights across digital transformation projects.
Responsibilities
- Collaborate with business and technical stakeholders to understand data requirements and develop modern data solutions
- Design, build, and maintain scalable data pipelines across on-premises and cloud platforms
- Develop, optimize, and maintain dimensional and other data models for analytics and reporting
- Integrate data from relational databases, NoSQL platforms, APIs, and files
- Enhance ETL/ELT processes through optimization, automation, and performance tuning
- Develop and operate end-to-end ETL/ELT workflows with validation, error handling, logging, monitoring, and scheduling
- Automate data pipeline deployment and operations through CI/CD practices
- Support governance of enterprise data platforms, data lakes, data warehouses, security controls, and access management
- Prepare curated data marts and fact/dimension tables to support analytics
- Analyze datasets to identify trends, patterns, and anomalies
- Develop interactive Power BI dashboards and reports and monitor key performance indicators
- Build predictive or descriptive models using statistical, Python, or R-based methods
- Present findings to non-technical audiences and translate complex data into actionable recommendations
- Deliver analytics solutions iteratively in an Agile environment
- Mentor teams to enhance analytics fluency and support self-service capabilities
- Provide data-driven analysis, visualizations, and AI-enabled insights for strategic decision-making
Requirements
- Strong foundation in data engineering practices
- Analytical skills to derive actionable insights from complex datasets
- Experience designing, building, and maintaining scalable data pipelines
- Knowledge of Azure, Databricks, Microsoft Fabric, GCP, and AWS
- Experience with dimensional data models, including star and snowflake schemas
- Experience integrating relational databases, NoSQL platforms, APIs, and files
- Knowledge of AI-enabled data integration techniques, schema discovery, metadata enrichment, and automated data quality validation
- Experience with ETL/ELT optimization, automation, and performance tuning
- Experience with SSIS, Azure/Fabric Data Factory, Dataflows, and Notebooks
- Knowledge of CI/CD, automated testing, release management, and monitoring
- Knowledge of data lakes, data warehouses, security controls, and access management
- Proficiency in DAX, Python, and R
- Experience developing Power BI dashboards and reports
- Experience building predictive or descriptive statistical or machine-learning models
- Experience delivering solutions in an Agile environment
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Degree requirement
No Education Requirement
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