Senior Data Engineer

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

📋 Description

• Collaborate with both business and technical stakeholders to grasp data requirements and develop cutting-edge data solutions.

• Design, construct, and sustain scalable data pipelines across on-premises and cloud environments.

• Create, enhance, and manage dimensional and other data models for analytics and reporting purposes.

• Integrate data from relational databases, NoSQL systems, APIs, and files.

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

• Develop and manage comprehensive ETL/ELT workflows that include validation, error handling, logging, monitoring, and scheduling.

• Automate the deployment and operation of data pipelines utilizing CI/CD methodologies.

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

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

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

• Create interactive Power BI dashboards and reports while monitoring key performance indicators.

• Develop predictive or descriptive models using statistical methods or programming languages like Python or R.

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

• Deliver analytics solutions iteratively within an Agile framework.

• Mentor teams to improve analytics proficiency and foster self-service capabilities.

• Provide data-driven analyses, visualizations, and AI-enhanced insights to inform strategic decision-making.

⛳️ Requirements

• Strong foundational knowledge of data engineering practices.

• Analytical capabilities to extract actionable insights from intricate datasets.

• Proven experience in designing, building, and maintaining scalable data pipelines.

• Familiarity with Azure, Databricks, Microsoft Fabric, GCP, and AWS.

• Experience with dimensional data models, including star and snowflake schemas.

• Proficient in integrating relational databases, NoSQL systems, APIs, and files.

• Understanding of AI-enabled data integration techniques, schema discovery, metadata enrichment, and automated data quality validation.

• Experience in optimizing, automating, and tuning ETL/ELT processes.

• Familiarity with SSIS, Azure/Fabric Data Factory, Dataflows, and Notebooks.

• Knowledge of CI/CD practices, automated testing, release management, and monitoring.

• Understanding of data lakes, data warehouses, security measures, and access management.

• Proficiency in DAX, Python, and R.

• Experience in developing Power BI dashboards and reports.

• Experience in building predictive or descriptive statistical or machine-learning models.

• Background in delivering solutions within an Agile environment.

🏝️ Benefits

• Comprehensive health benefits.

• Opportunities for professional development and training.

• Flexible work arrangements.

• Collaborative and innovative work environment.