Sr Data Engineer

Position: Senior Data Engineer

Location: Hybrid/Toronto

Job ID#: RQ00527

Duration: 6 months

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.

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

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).
  

Qualifications/Experience Required

• 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.
  

About Symbiotic Digital.

Symbiotic Digital provides the IT Experts you need that solve problems and get things done. See what the top 2% in their field can do for you. (Symbiotic Digital is a division of Symbiotic Group Inc.)

We serve customers in two ways, we

provide:

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Serving IT & Business leaders, Symbiotic Digital provides a business system that enable us to provide the Expert Technical staff needed to solve challenging business and IT problems. IT leaders in the most reputable organizations in Canada have relied on Symbiotic Digital to help them staff difficult assignments with proven Experts uniquely evaluated by our proven QMS- Quality Management System Staff Development Model. We are a 100% Indigenous owned company.

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