TI

Snowflake Data Engineer

Hiring from
Canada
Work type
Remote
Posted
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Role - Snowflake Data Engineer

Location: Remote (Anywhere in Canada)

Experience: 5-8 Years

Employment Type: Full-Time


Job Summary

We are seeking a talented Mid-Level Data Engineer to join our growing data team. The ideal candidate will have hands-on experience in building, optimizing, and maintaining scalable data pipelines and data warehouse solutions. You will work closely with business stakeholders, analytics teams, and data architects to deliver reliable and high-quality data solutions using Python, SQL, Snowflake, DBT, and a BI tool such as Power BI or Tableau.


Key Responsibilities

  • Design, develop, and maintain robust ETL/ELT pipelines using Python, SQL, and DBT.
  • Build and optimize data models within Snowflake to support analytics and reporting requirements.
  • Develop reusable and scalable data transformation frameworks using DBT.
  • Monitor, troubleshoot, and enhance existing data pipelines for performance and reliability.
  • Integrate data from multiple source systems into Snowflake data warehouses.
  • Collaborate with BI developers and business users to understand reporting requirements.
  • Support dashboard development and data visualization initiatives using Power BI or Tableau.
  • Implement data quality checks, validation processes, and monitoring mechanisms.
  • Optimize SQL queries and Snowflake workloads for improved performance and cost efficiency.
  • Participate in code reviews, documentation, and best practice adoption.


Required Skills

  • 5-8 years of experience in Data Engineering or related roles.
  • Strong programming experience in Python.
  • Advanced proficiency in SQL for data extraction, transformation, and optimization.
  • Hands-on experience with Snowflake Data Warehouse.
  • Strong experience with DBT (Data Build Tool) for data transformation and modeling.
  • Experience with Power BI or Tableau for reporting and data visualization.
  • Knowledge of ETL/ELT concepts and data warehousing principles.
  • Experience working with large-scale datasets and cloud-based data platforms.
  • Familiarity with Git and CI/CD practices.
  • Strong analytical and problem-solving skills.


Preferred Qualifications

  • Experience with cloud platforms such as AWS, Azure, or GCP.
  • Knowledge of orchestration tools such as Airflow, Prefect, or Azure Data Factory.
  • Understanding of data governance, data quality, and security best practices.
  • Exposure to Agile/Scrum development methodologies.


Education

  • Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related field.


Nice-to-Have Skills

  • Snowflake Performance Tuning
  • Data Modeling (Star Schema, Dimensional Modeling)
  • Data Lake Architecture
  • PySpark or Spark
  • API Integration Experience


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