Data Engineer​/Snowflake

Role:
Data Engineer / Snowflake Migration Specialist

location :

Toronto - Hybrid (4 Days WFO)

Design, develop, and maintain scalable and reliable data engineering pipelines to support analytics and business intelligence needs
Architect, design, and implement solutions that meet stakeholder's needs
Architect, implement, and optimize Snowflake data warehouse solutions, including data modeling, performance tuning, and cost optimization
Lead and support data migration initiatives, including migration from on-premises or legacy data platforms to Snowflake or other cloud-based solutions
Develop and manage ELT/ETL processes using modern data integration tools and frameworks
Participate actively in requirements gathering, data modeling, and design sessions
Prepare high-level and detailed technical specifications for the projects in accordance with security and architecture documentation objectives
Develop detailed plans and accurate estimates for the completion of the build, system testing, and implementation phases of a project
Collaborate with data architects, analytics teams, and business stakeholders to translate requirements into technical solutions
Running and optimizing SQL queries on RDBMS like MS SQL server, MySQL/MariaDB
Ensure data quality, security, governance, and compliance throughout the data lifecycle
Develop, code, document, and execute unit tests, systems, integration and acceptance tests, and testing tools for functions of high complexity
Troubleshoot and resolve performance, data integrity, and pipeline reliability issues
Document architecture, data flows, and operational procedures

What do you need to succeed?
Must-have
Strong hands-on experience in Data Engineering, including data pipeline development and large-scale data processing
Deep expertise in Snowflake architecture, including Virtual warehouses, Micro-partitioning, Clustering and performance optimization, Security and access control
Proven experience with data migration projects, including assessment, planning, execution, and validation
Minimum 5+ years of experience in software engineering or analytics in creating enterprise data architectures, distributed and microservice software architectures and design patterns
Strong SQL skills and experience with data modeling (dimensional and/or data vault)
Core SQL database concepts, including creating DDL, DML scripts, normalization, running, and optimizing SQL queries on RDBMS
Experience working with cloud platforms (AWS, Azure, or GCP)
2+ years of application development experience in Hadoop, No

SQL databases like Mongo

DB, Cassandra, or HBase
Familiarity with orchestration and data integration tools (e.g., Airflow, dbt, Informatica, Fivetran, or similar)
Prior experience with Liquibase, Git code repos like Git Hub
Bachelor's degree in information technology, Computer Science
Strong problem-solving skills and ability to work independently in a fast-paced environment