Senior Data Engineer Risk Technology

iTech US, Inc.; Toronto; Hybrid; CAD 80,000 - 100,000; Full time

Job summary

A leading technology firm is seeking a Sr. Data Engineer in Toronto, Canada (Hybrid) to design and build cloud-based data pipelines and troubleshoot production issues. The ideal candidate will have 6-12 years of experience in complex environments, hands-on AWS data services expertise, and strong SQL skills. The role emphasizes building resilient data systems to support risk analytics, drive automation, and collaborate with multiple stakeholders to enhance delivery standards and improve data quality.

Qualifications

• 6-12 years of experience as a Data Engineer is required.
• Experience in complex, enterprise environments is crucial.
• Hands-on knowledge of cloud-native architectures is necessary.

Responsibilities

• Design and build cloud-based data pipelines supporting risk and analytics.
• Troubleshoot production data issues and conduct root-cause analysis.
• Collaborate with stakeholders to develop durable solutions.

Skills

AWS data services expertise

SQL skills

Data processing skills

Problem-solving mindset

Education

Bachelor's degree in Computer Science, Software Engineering, or related field

Tools

Airflow

Job description

Position: Sr. Data Engineer — Risk Technology

Location: Toronto, Canada (Hybrid)

Contract: 12 Months

Must Have: 6-12 years exp ideally. AWS expertise still a key focus

Job Description

Role Overview

We are seeking experienced Data Engineers to strengthen הדין data platform and execution capabilities. The role focuses on building resilient, scalable data pipelines while reducing operational friction and improving delivery discipline. This position is critical to enabling reliable risk analytics and supporting long-term technology modernization initiatives.

Key Responsibilities

• Design, build, and maintain cloud-based data pipelines supporting risk and analytics use cases
• Own and troubleshoot production data issues, performing root-cause analysis rather than reactive reruns
• /analyze? Improve data quality, validation, and control frameworks, particularly around configuration and inputs
• Enhance orchestration and scheduling platforms (e.g., Airflow), including upgrades and stability improvements
• Partner with business and risk stakeholders to understand “why” behind requests and propose durable solutions
• Reduce manual operational effort through automationസ്ഥാന self‑service workflows, and auditability
• Contribute to planning, estimation, and delivery discipline for technology initiatives
• Support a hybrid operating model alongside offshore teams while driving higher standards of ownership and execution

Required Skills & Experience

• Strong experience as a Data Engineer in complex, enterprise environments
• Hands‑on expertise with AWS data services and cloud‑native architectures
• Proven experience building and operating large‑scale data pipelines
• Solid knowledge of workflow orchestration tools (Airflow or equivalent)
• Strong SQL and data processing skills; experience with structured and semi‑structured data
• Demonstrated ability to diagnose issues end-to-end and implement permanent fixes
• Experience working in regulated, risk, or financial services environments preferred

Key Attributes

• Strong critical thinking and problem‑solving mindset
• Comfortable challenging requirements and asking the right questions before execution
• Ability to balance production support with strategic engineering work
• Proactive, ownership‑driven approach to delivery
• Clear communicator able to collaborate across technology and business teams

Education: At least a bachelor’s degree (or equivalent experience) in Computer Science, Software/Electronics Engineering, Information Systems, or closely related field is required.