The Opportunity
The Data Engineer is responsible for designing, building, and maintaining scalable data pipelines and data assets that support data-driven decision making across the organization. Working closely with cross-functional data teams, they integrate new data sources into existing data products while leveraging GCP technologies to manage and process large-scale datasets. The role focuses on developing reusable, configurable, and efficient data pipeline frameworks, as well as producing clean, modular, and well-documented code that enhances collaboration, reduces operational overhead, and accelerates future development.
What to Expect
- Data Ingestion and Processing: Design and implement robust data pipelines to collect, clean, transform, and store large volumes of data using GCP services like BigQuery and Cloud Storage, as well as DataBricks
- Data Warehousing and Analytics: Build and optimize data warehouses on Google BigQuery for efficient data analysis and reporting.
- Data Modeling: Design and implement scalable data models to support strategic data products, business intelligence, and machine learning applications.
- ETL/ELT Development: Develop and maintain Extract, Transform, Load (ETL) or Extract, Load, Transform (ELT) processes using GCP tools.
- Performance Optimization: Continuously monitor and optimize data pipelines and queries for performance and cost-effectiveness.
- Collaboration: Work closely with data scientists, analysts, and other stakeholders to understand data requirements and deliver data solutions.
What you Bring:
- Google Cloud Platform (GCP): Strong proficiency in GCP data services, including BigQuery, Cloud Storage, and DataBricks. Experience with Dataflow is an asset.
- Bachelor's or Master's degree in Math, Computer Science, Software Engineering, or a related field.
- Minimum 3-5+ years of experience in a hands-on data engineering role, with a focus on pipeline development and data modeling on Google Cloud Platform.
- Experience with large-scale data processing and distributed systems.
- Google Cloud Professional Data Engineer Certification or equivalent is a strong asset for this role.
- Strong data engineering expertise, building and orchestrating scalable data pipelines using Airflow, Cloud Composer, Apache Beam, and Python.
- Advanced SQL and data modeling skills, including complex query development, optimization, schema design, and data analysis.
- Proven ability to develop dynamic Airflow DAGs and robust data solutions that support efficient, reliable data processing.
- Solid understanding of Agentic AI
Salary Range: $92,000-$142,000
Actual salary for the role may vary depending on work location of the successful candidate and other factors including but not limited to, skills, education, experience, working conditions and the local labour market.
This position is being posted to fill an existing vacancy.
We also take potential into consideration. If you don’t have this exact experience, but you know you have what it takes, be sure to give us more insight through your application and cover letter.
Our inclusive work environment welcomes diversity and supports accessibility. If you require accommodation at any time during the recruitment process, please let us know by contacting [email protected].
As part of Definity’s commitment to reconciliation, we acknowledge that our work, meetings, and travel take place on the lands now known as Canada, and recognize the enduring presence, wisdom, and stewardship of the First Nations, Métis, and Inuit peoples who have long cared for these lands.
Background checks
This role requires successful clearance of a background check (including criminal checks and leadership references).
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