Data Engineer/ Data Analyst

Role: Data Engineer/ Data Analyst

Location: Toronto, Ontario, Canada (M5J 0E6)

Please note that this opportunity is open only to candidates currently based in Canada. If you meet this requirement, I encourage you to apply.

Overview We are seeking a detail-oriented Data Engineer/ Data Analyst to support data processing, reporting, and insights across our organization. This role is ideal for someone early in their analytics career who is eager to grow, contribute to business decisions, and work cross-functionally with teams across the organization.

Key Responsibilities:

• Collect, clean, and analyze structured datasets to support operational and strategic initiatives.
• Build and maintain dashboards, reports, and data visualizations that clearly communicate key trends and findings.
• Write, optimize, and troubleshoot SQL queries for data extraction, transformation, and validation.
• Assist in developing Python-based scripts, workflows, and analytical models to automate recurring tasks and enhance data accuracy.
• Support data quality, documentation, and governance efforts across the data lifecycle.
• Partner with cross-functional teams to understand requirements, translate business questions into data solutions, and deliver actionable insights.
• Contribute to improving internal analytics processes and identifying opportunities for efficiency.

Required Qualifications:

• 2 3 years of hands-on experience working with data in a professional or project-based environment.
• Proficiency in SQL for querying and manipulating relational datasets.
• Practical experience using Python for analysis, automation, or data manipulation.
• Foundational understanding of Snowflake or other cloud-based data warehousing platforms.
• Strong analytical thinking, problem-solving skills, and attention to detail.
• Ability to synthesize information and communicate insights clearly to non-technical audiences.

Preferred Qualifications:

• Exposure to facilities, workplace operations, real estate, or related environments.
• Experience with BI tools (e.g., Streamlit, Tableau, Power BI).
• Familiarity with version control (e.g., Git) and collaborative development workflows.