About this role
Job Title: Senior Spark Data Engineer Location: Hybrid (2 days), Toronto, Canada Experience: 5+ Years Rate: 60 CAD to 70 CAD per hour Role Summary We are hiring for the Senior Data Engineer role, where the selected candidate will work on scalable data pipelines and analytics solutions. This position focuses on large-scale data processing, insights generation, and business decision support. Key Responsibilities Design and build scalable data pipelines (batch and real-time) Translate business requirements into data architectures Solve complex data engineering problems with iterative solutions Build and maintain high-volume data infrastructure Automate cloud workflows, infrastructure, and monitoring Develop CI/CD pipelines to improve deployment and quality Collaborate with data scientists, product managers, and analysts Perform data analysis and data mining for business insights Create dashboards, reports, and KPI tracking systems Deliver ad-hoc analysis and long-term data projects Define and monitor critical business metrics and KPIs Present insights to technical and non-technical stakeholders Must-Have Skills Strong experience with Python, Spark (PySpark, Spark SQL), and SQL Hands-on experience with Snowflake and Hive Experience building ETL pipelines using Airflow Strong understanding of data modeling and analytical data systems Experience with BI tools: Power BI, Tableau, or Qlik Strong coding skills with clean, maintainable code practices Experience with Git and CI/CD tools (e.g., Jenkins) Familiarity with Jupyter, Zeppelin, or similar notebook environments Nice-to-Have Skills Experience with Looker Exposure to Tableau or Qlik Familiarity with AWS services and distributed systems Experience with Presto or similar query engines Certifications Cloud or Data Engineering certifications are a plus Apply now or share your resume at [email protected],