RQ00527 -Cloud Data Engineer - Ontario One Call

RQ00527 - DataOps/Cloud Data Engineer - Ontario One Call

Location: Up to 2 days onsite (subject to HM’s discretion)

Feedback from HM:

Following the interviews, we found that while the candidates demonstrated solid experience in data analysis from a Business Analytics perspective, they did not fully meet the expectations for a senior-level data engineering role. Specifically, we are looking for stronger end-to-end engineering capabilities including independently designing, building, optimizing, and supporting production-grade data pipelines.

In addition, we were hoping to see a more polished, professional, and proactive approach in articulating technical decisions and ownership of engineering solutions.

For upcoming submissions, we would like to prioritize candidates with:

Updated Must Haves:

• Minimum 7 years Demonstrated hands-on experience building and maintaining end-to-end data pipelines in production
• Minimum 7 years Strong expertise in SQL and Python from an engineering standpoint
• Minimum 7 years Experience implementing data quality controls, monitoring, and troubleshooting with minimal escalation
• Minimum 7 years Practical experience with modern data platforms (e.g., Microsoft Fabric or similar enterprise environments)

Location: Up to 2 days onsite (subject to HM’s discretion)

Shortlist Date: 2026-03-04, 12:00 p.m.

Start Date

2026-02-23

End Date

2026-08-23

Business Days

130.00

DataOps/Cloud Data Engineer - Senior

Office Location

104 Cooper Dr Suite 1, Guelph, ON N1C 1C3

Position Overview

Ontario One Call is seeking a highly technical Senior Data Engineer to support the Manager, Data Engineering and AI Enablement in building and operating reliable, production-grade data pipelines and analytics foundations.

This role is hands on and delivery focused. The Senior Data Engineer is responsible for implementing data pipelines, transformations, and data quality controls using Microsoft Fabric, SQL, and Python. The role supports enterprise reporting, operational analytics, and data driven decision making by ensuring data is accurate, timely, and trusted.

The successful candidate will demonstrate strong engineering discipline, accountability for deliverables, and the ability to work independently within established direction and standards set by the Manager.

Key Responsibilities

· Design, build, and maintain end to end data pipelines using Microsoft Fabric, including Lakehouse, Data Factory, Dataflows, and notebooks.

· Develop and optimize SQL based transformations, data models, and curated datasets for enterprise reporting and analytics.

· Build and maintain Python based data engineering logic for ingestion, transformation, validation, and automation.

· Implement and operate data quality controls, including validation rules, reconciliation checks, and exception handling.

· Monitor data pipelines, investigate failures or data quality issues, and implement fixes with minimal escalation.

· Integrate data from multiple enterprise systems, including CRM, ticketing systems, telephony platforms, and operational databases.

· Maintain technical documentation, data lineage, and operational runbooks for owned pipelines and datasets.

· Work closely with the Manager and Data Analysts to ensure data assets meet defined standards and reporting requirements.

Required Qualifications and Experience

· Minimum 7 years of hands-on experience in data engineering or analytics engineering roles.

· Strong, practical experience with Microsoft Fabric in a production environment.

· Advanced proficiency in SQL, including complex transformations and performance optimization.

· Strong hands-on experience using Python for data engineering and automation.

· Demonstrated experience implementing data quality controls and operating reliable data pipelines.

· Experience working in cloud-based data platforms and modern data architectures.

· Ability to deliver independently while aligning to technical direction and priorities set by management.

· Microsoft certifications preferred such as Microsoft certified Fabric analytics engineer, Azure data engineer or Microsoft data platform certification.

Preferred Qualifications

· Degree in Computer Science, Engineering, or a related technical field.

· Experience supporting Power BI semantic models and enterprise reporting environments.

· Familiarity with Git, version control, and basic CI/CD practices for data engineering.

· Experience working in regulated, operational, or public sector environments.