Senior Data Engineer (Snowflake)
New
A
APPLYCustomer Experience AI
Toronto / Vancouver / Canada. The preferred candidate should be based in either the Greater Toronto Area or the Greater Vancouver Area of Canada, ET (Eastern Timezone) or PT (Pacific Timezone)Full-TimeSenior
Salary not disclosed
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Job Details
- Languages
- English
- Experience
- 5+ years
- Required Skills
- PythonSQLApache AirflowETLSnowflakeData modelingdbt
Requirements
- Certified SnowPro.
- 5+ years of experience in data engineering, building modern cloud-based data platforms.
- Strong hands-on experience with Snowflake, including performance tuning, security, and data modeling.
- Advanced SQL skills for analytics engineering and data transformation.
- Proficiency in Python for data processing, automation, and orchestration.
- Experience with dbt or similar analytics engineering frameworks.
- Familiarity with orchestration tools such as Dagster or Apache Airflow.
- Experience enabling or supporting machine learning, feature engineering, or AI-driven use cases on top of data platforms.
- Solid understanding of data privacy, governance, and compliance best practices.
- Strong problem-solving skills and a pragmatic, delivery-oriented mindset.
- Experience collaborating with distributed teams across North America and Latin America.
- Excellent English communication and collaboration skills.
Responsibilities
- Design, build, and maintain scalable data pipelines and architectures to support analytical and operational workloads.
- Develop and optimize ETL/ELT pipelines, ensuring efficient data extraction, transformation, and loading from various sources.
- Work closely with backend and platform engineers to integrate data pipelines into cloud-native applications.
- Manage and optimize cloud data warehouses, primarily BigQuery, ensuring performance, scalability, and cost efficiency.
- Implement data governance, security, and privacy best practices, ensuring compliance with company policies and regulations.
- Collaborate with analytics teams to define data models and enable self-service reporting and BI capabilities.
- Develop and maintain data documentation, including data dictionaries, lineage tracking, and metadata management.
- Monitor, troubleshoot, and optimize data pipelines, ensuring high availability and reliability.
- Stay up to date with emerging data engineering technologies and best practices, continuously improving our data infrastructure.
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