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Location
In office (Toronto)
Seniority
Staff
Employment
Contractor

Confirmed on the employer's own hiring board on Nov 8, 2026. First seen by Alion on May 28, 2026. Querentia scores C on the Alion truth index.

Overview
Company
Impact
Profile match
Querentia is a recruitment and talent solutions firm headquartered in Toronto that places technology and non-technology professionals with client organisations across North America. Established in 2021 as Querentia Inc., the firm also lists offices in New York, San Jose and Dover, Delaware, and fills contract and permanent roles for clients in Toronto, Montreal, Vancouver, Ottawa and Calgary. Its open assignments are mostly IT contracts such as SAP and Workday consultants, Databricks and GCP data engineers, Salesforce consultants, enterprise and solution architects, computer vision and AI engineers, program managers and digital marketing specialists.
Job Summary

We are seeking a highly experienced GCP Data Engineering Lead to provide senior technical leadership and delivery management for enterprise-scale cloud data engineering initiatives. The ideal candidate will combine deep hands-on expertise in Google Cloud Platform data pipeline architecture with strong Agile delivery and quality assurance leadership.

This role will be responsible for leading end-to-end pipeline architecture, QA strategy, sprint execution, technical governance, and offshore team coordination across high-volume data ingestion and analytics environments.

Key Responsibilities

Technical Leadership & Architecture

  • Lead pipeline architecture design for Netscout and Sandvine ingestion pipelines.
  • Design scalable data ingestion and transformation workflows using:
  • GCS landing zones
  • Google Cloud Dataflow
  • Google BigQuery
  • Bronze/Silver/Gold Medallion architecture layers
  • Define Medallion Architecture data flow standards and transition rules.
  • Lead data reconciliation and parity validation strategies across enterprise data platforms.
  • Provide hands-on support for complex transformation logic and pipeline optimization.

QA & Data Quality Management

  • Define and own end-to-end QA strategy for data pipelines including:
  • Test coverage
  • Quality gates
  • Defect management
  • Governance validation
  • Architect reusable test templates for batch and streaming pipelines.
  • Define data quality specifications for each Medallion layer.
  • Review and assure quality of all pipeline and QA deliverables.

Delivery & Team Management

  • Lead Agile sprint planning, sprint reviews, and retrospectives.
  • Maintain RAID logs (Risks, Assumptions, Issues, Dependencies) and drive mitigation activities.
  • Produce weekly delivery status reports and maintain project trackers.
  • Coordinate with client engineering teams on environments, access, and technical decisions.
  • Manage offshore Data Engineers and Observability Engineers including task allocation and quality oversight.
  • Drive mentoring, knowledge transfer, and delivery excellence initiatives.

Required Qualifications

  • Advanced experience with Google Cloud Platform data engineering services including:
  • Google BigQuery
  • Google Cloud Dataflow / Apache Beam
  • Pub/Sub
  • GCS
  • Strong hands-on development expertise in Python and SQL.
  • Experience designing QA frameworks for cloud data pipelines using tools such as Great Expectations or dbt tests.
  • Strong understanding of Medallion Architecture and enterprise data processing patterns.
  • Experience leading Agile delivery processes and technical project governance.
  • Strong stakeholder communication and team leadership skills.

Preferred Qualifications

  • Advanced Google Cloud Platform certifications.
  • Telecom, telemetry, or high-volume streaming data experience.
  • Experience with observability and data governance frameworks.
  • Prior experience managing offshore delivery teams.
  • Strong mentoring and knowledge transfer capabilities.

Key Skills & Competencies

  • GCP Data Engineering
  • BigQuery & Dataflow
  • Apache Beam & Pub/Sub
  • Medallion Architecture
  • Data Pipeline QA & Governance
  • Python & SQL Development
  • Agile Delivery Management
  • Data Quality & Reconciliation

• Team Leadership & Stakeholder Management

Skills

GCP, Data Engineering

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