OPEN: Data Analytics Developer

We are currently requesting resumes for the following position: Data Analytics Developer

Resume Due Date: Friday, April 04, 2025 (5:00PM EST)

Job ID: 25-048

Number of Vacancies: 2

Level: MP4

Duration: 8 Months

Hours of work: 35 Hours per week

Location: 700 University Avenue, Toronto

Work Mode: 100 % remote

Job Overview

About the Role:

• We are seeking an experienced Data Analytics Developer to support a growing portfolio of analytics use cases across enterprise functions.
• This role requires hands-on expertise in SQL-based data curation, data modeling, and Power BI dashboard development, with potential to support data science work utilizing Python-based tools.
• You will work within an Azure and Databricks environment, collaborating closely with business stakeholders, data stewards, and internal data teams.

Key Responsibilities:

• Design, develop, and deploy advanced data analytics solutions using SQL, Python, and Power BI.
• Perform data curation and enrichment activities using structured enterprise data sets.
• Build optimized and reusable data models for analytics and reporting.
• Support development of analytics for key initiatives.
• Work within an Azure Data Lake and Databricks ecosystem, integrating curated datasets.
• Collaborate with internal data teams and SMEs to gather requirements and deliver actionable insights.
• Ensure accuracy, reliability, and performance of developed analytics solutions.

Qualifications:

• 5+ years of experience in data analytics and business intelligence development.
• Expert-level SQL skills, with proven experience in data wrangling, enrichment, and modeling.
• Proficiency in Power BI dashboard creation and visual storytelling.
• Experience working in Azure analytics environments (e.g., Data Lake, Synapse, Azure SQL, Databricks).
• Strong understanding of data pipelines and ETL/ELT workflows.
• Exposure to Python and machine learning libraries is an asset (not required but preferred).
• Ability to interpret business requirements and translate them into technical specifications.
• Strong communication and collaboration skills.

Assets:

• Familiarity with enterprise data governance practices and metadata tools.
• Previous work in highly regulated or enterprise-level environments.