Data Engineer

Position Overview

Shyft Labs is a rapidly growing data product company founded in 2020. We specialize in building high-impact digital solutions for Fortune 500 companies, focusing on accelerating business growth through technical innovation.

We are seeking a skilled and passionate Data Engineer with deep expertise in Google Cloud Platform (GCP) and Google Big Query to join our Toronto team. In this role, you will architect, build, and maintain the scalable data pipelines that serve as the foundation for our analytics and data science initiatives. You will own the entire data lifecycle right from ingestion and processing to warehousing and serving, creating a reliable ecosystem that empowers business leaders to make data-informed decisions.

• Data Architecture & Pipeline Development:
  Design, build, and maintain scalable and reliable batch and real-time ETL/ELT data pipelines using GCP services like Dataflow, Cloud Functions, Pub/Sub, and Cloud Composer.
• Data Warehousing:
  Develop and manage our central data warehouse in Google Big Query. Implement data models, schemas, and table structures optimized for performance and scalability.
• Data Processing & Transformation:
  Write clean, efficient, and robust code (primarily in SQL and Python) to transform raw data into curated, analysis-ready datasets.
• Infrastructure Optimization & Scalability:
  Monitor, troubleshoot, and optimize our data infrastructure for performance, reliability, and cost-effectiveness. Implement Big Query best practices, including partitioning, clustering, and materialized views.
• Enable Data Accessibility & BI:
  Build and maintain curated data models that serve as the "source of truth" for business intelligence and reporting, ensuring data is ready for consumption by BI tools like Looker.
• Data Governance & Quality:
  Implement automated data quality checks, validation rules, and monitoring to ensure the accuracy and integrity of our data pipelines and warehouse.
• Collaboration:
  
  Work closely with software engineers, data analysts, and data scientists to understand their data requirements and provide the necessary infrastructure and data products.

• Experience:
  
  3-5+ years of hands‑on experience in a Data Engineering, Software Engineering, or a similar role.
• Programming
  
  Skills:
  
  Strong proficiency in a programming language such as Python or Java for data processing and automation.
• Expert SQL Proficiency:
  Mastery of SQL for complex data manipulation, DDL/DML operations, and query optimization.
• Google Big Query:
  Proven expertise in using Big Query as a data warehouse, including data modeling, performance tuning, and cost management.
• GCP Data Services:
  Hands‑on experience building data pipelines using the GCP ecosystem (e.g., Dataflow, Pub/Sub, Cloud Storage, Cloud Composer/Airflow).
• Data Pipeline Concepts:
  Deep understanding of ETL/ELT principles and data warehousing architecture (e.g., Star Schema, Data Lakes).
• Engineering Mindset:
  Strong problem‑solving and troubleshooting skills with a focus on building scalable, maintainable, and automated systems.

• BI Tool Integration:
  Experience building data models that power BI tools like Looker (knowledge of LookML is a strong plus), Tableau, or Power BI.
• Modern Data Stack Tools:
  Experience with tools like dbt, Dataform, or Fivetran for data transformation and integration.
• Infrastructure as Code (IaC):
  Familiarity with tools like Terraform or Deployment Manager for managing cloud infrastructure.
• Containerization:
  Knowledge of Docker and Kubernetes is a plus.
• Certifications:
  
  Google Cloud Professional Data Engineer certification is highly desirable.
• Version Control:
  Proficiency with Git for code management and CI/CD pipelines.

At Shyft Labs, your work matters. We’re a growing data product company making a big impact with Fortune 500 clients and as we scale, you’ll have the chance to shape solutions, influence strategy, and grow your career alongside us.

Here’s what you can expect when you join our team:

• Hybrid Flexibility:
  Enjoy a hybrid model with 3+ days per week in our Toronto office.
• Downtown Toronto Office:
  Work in the heart of…