Posted 22 days ago
GCP Senior Data Engineer Grade
@ Querentia Inc.
Remote in Canada
Overview
Querentia Inc. is hiring a GCP Senior Data Engineer on a contract basis, fully remote in Canada. The role leads a team of 10 data engineers building scalable pipelines and cloud data infrastructure on Google Cloud Platform, with code reviews, engineering standards and support for analytics and machine learning.
Responsibilities:
- Lead a team of 10 data engineers
- Build and optimize ETL/ELT pipelines on GCP
- Architect BigQuery, Cloud Storage and Data Fusion infrastructure
- Implement CI/CD, infrastructure as code and monitoring
- Optimize performance and GCP costs
Requirements summary:
- Proven leadership of onshore and offshore data engineering teams
- Proficiency in SQL, Python, Java/Scala
- Hands-on GCP experience with BigQuery, Dataflow, Dataproc, Pub/Sub, Composer, Terraform
- Familiarity with CI/CD and Git
- Experience building and optimizing data pipelines
Tools & skills
Source and dates
Source type not verified · jsonld
- Employer posting date
- 2026-10-15
- First seen by our source
- 2026-10-26
- Source record updated
- 2026-11-05
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Senior |
| Department | Software development |
| Manages people | Yes |
| Travel | air: none · ground: none |
| Work setting | Home |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
Summary and details written by AI from the posting; the employer’s posting is the authority.
Querentia Inc.
| Field | Value |
|---|---|
| Open jobs on Jobsy | 331 |
GCP Senior Data Engineer Grade
Work Location: Canada (Remote)
Job Summary
The GCP Senior Data Engineer will lead a team of 10 data engineers in designing, developing, and optimizing scalable data pipelines and cloud-based data infrastructure on Google Cloud Platform (GCP). This is a leadership-focused role requiring experience managing onshore and offshore teams, establishing engineering standards, and delivering reliable data solutions to support analytics and machine learning use cases.
Key Responsibilities
•
Pipeline Development: Build and optimize ETL/ELT pipelines using Dataflow (Apache Beam), Dataproc (Spark), Pub/Sub, and Cloud Functions.
•
Data Infrastructure: Architect and manage BigQuery, Cloud Storage, and Data Fusion for efficient data ingestion, transformation, and storage.
•
Team Leadership: Lead a team of 10 engineers, conduct code reviews, and establish data engineering standards.
•
DevOps & Monitoring: Implement CI/CD practices, infrastructure-as-code, and monitoring using Cloud Monitoring and Cloud Logging.
•
Performance & Cost Optimization: Improve pipeline performance and query efficiency while managing GCP costs through techniques such as slot reservations and partitioning.
•
Collaboration: Work with data architects, data scientists, and analysts to deliver self-service data platforms and support advanced analytics and machine learning use cases.
•
Data Quality & Governance: Implement data validation, lineage, and metadata management using tools such as Data Catalog and dbt.
Required Qualifications
•
Leadership: Proven experience leading data engineering teams across onshore and offshore locations. Candidates must have leadership experience; this is not an individual contributor-only role.
•
Programming & Distributed Systems: Proficiency in SQL, Python, Java/Scala, and distributed processing frameworks such as Spark and Beam.
•
GCP Expertise: Hands-on experience with BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer (Airflow), and Terraform.
•
DevOps: Familiarity with CI/CD, Git, and infrastructure-as-code practices.
•
Data Engineering: Experience building and optimizing data pipelines, managing cloud data infrastructure, and implementing data quality and monitoring practices.
Nice to Have
•
GCP certifications, such as Google Cloud Professional Data Engineer.
•
Experience with real-time data processing.
•
Familiarity with Vertex AI and machine learning workflows.
•
Experience working in multi-cloud environments.
Journal
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