Senior Data Engineer

This is a fully remote position, open to applicants in Canada.

📋 Description

• Design, construct, and maintain scalable data pipelines across both on-premises and cloud environments, including Azure, Databricks, Microsoft Fabric, GCP, and AWS.

• Develop, optimize, and sustain data models, including dimensional structures such as star and snowflake schemas.

• Integrate data from relational databases, NoSQL systems, APIs, and files using data integration methodologies, such as intelligent data mapping, schema discovery, metadata enhancement, and automated data quality validation.

• Improve ETL/ELT processes through optimization, automation, and performance tuning.

• Create and manage end-to-end ETL/ELT workflows utilizing SSIS, Azure/Fabric Data Factory, Dataflows, and Notebooks.

• Implement data validation, error handling, logging, monitoring, and scheduling processes.

• Automate the deployment and operations of data pipelines through CI/CD practices, automated testing, release management, and monitoring.

• Support the management and governance of enterprise data platforms, including data lakes, data warehouses, security controls, and access management.

• Collaborate with architects, developers, and stakeholders to convert requirements into technical solutions.

• Prepare curated data marts and fact and dimension tables to facilitate analytics.

• Analyze datasets to uncover trends, patterns, and anomalies.

• Utilize statistical methods, DAX, Python, and R to derive business insights.

• Create interactive Power BI dashboards and reports, incorporating calculated columns and measures.

• Develop predictive and descriptive models using statistical, Python, or R-based machine learning techniques.

• Present findings to non-technical audiences and translate complex data into actionable insights.

• Deliver analytics solutions within an Agile environment.

• Promote analytics adoption and self-service capabilities.

• Provide data-driven analysis, visualizations, and AI-enabled insights to support priorities and strategic initiatives.

⛳️ Requirements

• Bachelor’s degree in Computer Science, Information Technology, Engineering, Mathematics, or a related discipline.

• 5 years of experience as a Data Engineer and/or Data Analyst.

• 5 years of experience in Python, including PySpark, and SQL.

• 4 years of experience in Business Intelligence and Executive Reporting, including executive dashboards.

• 4 years of experience with Cloud or Hybrid Data Platforms and cloud modernization initiatives.

• 4 years of experience in Data Warehouse and Lakehouse Design.

• 4 years of experience with ETL processes and tools.

• 2 years of experience in Data Migration and Modernization.

• Three (3) professional references for similar work performed must be included with the resume.

• Preferred: 1 year of experience with AI-Assisted Development Tools and Practices.

• Preferred: 2 years of experience with DevOps, CI/CD, and Infrastructure as Code.

• Preferred: 1 year of experience with modern data technologies such as Microsoft Fabric.

• Preferred: 2 years of experience supporting enterprise-scale public sector environments.

🏝️ Benefits

• 12-month contract with a maximum extension term of 24 months.

• Full-time schedule of 36.25 hours per week.

• Remote work arrangement.