Cloud Snowflake Data Engineer

We are currently looking for a strong Cloud Snowflake Data Engineer for our client in Montreal, QC. Please find the detail description below. Kindly let me know your interest.

Job Title: Cloud Snowflake Data Engineer
Location - Montreal - Local candidates only --FACE TO FACE IS REQUIRED
Duration: Long term

Required qualifications, capabilities, and skills:

• Minimum of 7-10 years in a Data Warehouse Architecture and Development or data modeling role.
• Proven experience with data warehousing solutions, ELT processes, and data integration techniques.
• Expert level knowledge of SQL and experience with database management systems (e.g., Snowflake, Teradata, PostgreSQL, Sybase, DB2, etc.).
• Proficiency in data modeling tools like Erwin, Power-Designer, or equivalent tools.
• Familiarity with big data technologies and cloud services (AWS, Azure, Google Cloud).
• Exceptional analytical and problem-solving capabilities.
• Strong communication skills to articulate complex data concepts to non-technical stakeholders.
• Ability to work in a collaborative, agile environment.

Key Responsibilities

• Data Architecture Design:
• Develop and implement comprehensive data architecture strategies that support the needs of our Data on Snowflake Cloud Architecture.
• Design scalable data models that facilitate efficient data procurement, storage, processing, and analysis.

Data Modeling:

• Create logical and physical data models, that reflect business data consumption needs.
• Ensure data models to support data mining, business intelligence, and analytics activities and AI tools.
• Semantic models to facilitate self-service operations

Data Governance and Quality:

• Help establish and facilitate management of data definitions, standards, policies, and procedures.
• Enhance data quality by setting up frameworks for data consistency, accuracy, and completeness.
• Lead efforts in data cataloging for improved data discovery and understanding.

Collaboration:

• Work closely with data engineers, analysts, product owners, and other stakeholders to deliver data products that align with business objectives.
• Facilitate cross-functional team efforts to ensure data architecture supports all aspects of the business.

Tool Utilization and Expertise:

• Utilize advanced data modeling tools to design and optimize data architectures.
• Stay updated with the latest trends in data technology and methodologies applicable to asset management.
• Familiarity with business intelligence tool set ecosystem, and strong experience with some.