Data and Analytics Engineer

Summary:

• Experience Level: Level 3 (senior): 5-7 years
• Open positions: 1
• Location: Montreal
• Work Mode: Day 1 onboarding onsite / in office presence 3x week

Responsibilities:

• Hands-on development, data pipeline creation, and collaboration with stakeholders across the organization.
• Drive decision-making and business insights through specialist data analysis and expertise.
• Craft data pipelines, implement data models, and optimize data processes for improved data accuracy and accessibility.
• Apply machine learning and AI-based techniques.

Requirements:

• Experience in data engineering or a related field.
• Design and implement data pipelines and workflows to support analytics and reporting needs.
• Develop interactive dashboards and reports using visualization tools like Power BI and Tableau.
• Collaborate with business stakeholders to understand requirements and translate them into data models and visualizations.
• Utilize Dataiku and other analytics platforms for data preparation, machine learning workflows, and advanced analytics.
• Ensure data quality, integrity, and security across all analytics solutions.
• Optimize performance of dashboards and queries for large datasets.
• Stay updated on emerging trends in data analytics and visualization technologies.
• Experience working on Snowflake and Databricks (Min one of the two).
• Knowledge of database systems (SQL and NoSQL).
• Experience on Snowflake Cortex appreciated.
• Familiarity with cloud platforms (AWS, Azure) and their data services.
• Experience using Jupyter notebooks for data exploration, analysis, and visualization.
• Excellent communication and collaboration skills.
• Ability to work independently and as part of a geographically distributed team.

Preferred Skills:

• Familiarity with programming skills in Python.
• Experience with data warehousing concepts and technologies.
• Familiarity with data governance and security best practices (e.g., data access control, data masking).
• Experience with Agile methodologies.
• Familiarity with data catalog and metadata management tools (e.g., Collibra).
• Familiarity with CI/CD pipelines and DevOps practices.

Benefits:

• Integrity and ownership, good team player.
• Ability to work under time and resource dependencies and constraints.
• Ability to find simple and effective solutions.
• High degree of motivation to expand technical and business knowledge.