Principal Engineer (Python/Azure)

TL;DR

Principal Engineer (Python/Azure): Providing technical leadership and operational ownership for the CPS DataValidation platform supporting OmniShopper and Homescan solutions with an accent on platform reliability, scalability, and modernization of hybrid on-premise and Azure ecosystems. Focus on designing scalable data architectures, managing production incidents, and optimizing high-volume ETL pipelines.

Location: Must currently reside in Canada and work within the Eastern Time Zone

Salary: CAD 112,700 - 140,000 per year

Company

NIQ is the world’s leading consumer intelligence company, delivering a complete understanding of consumer buying behavior through advanced analytics platforms.

What you will do

• Own the overall health, reliability, performance, and scalability of the DataValidation platform.
• Define and execute the technical strategy and roadmap for hybrid on-premise and Azure-based systems.
• Lead incident management, root cause analysis, and post-incident remediation activities.
• Review system designs and provide technical guidance to development teams to balance technical debt with delivery.
• Collaborate with Data Science, PMO, and Product Leadership to translate business requirements into technical solutions.
• Drive improvements in observability, monitoring, alerting, and operational KPIs.

Requirements

• 10+ years of software engineering experience.
• 5+ years in Staff Engineer, Principal Engineer, or Architect leadership roles.
• Must be based in Canada (Eastern Time Zone).
• Strong hands-on experience with Python, Oracle Database, and Linux environments.
• Expertise in Azure Data Services, PySpark, Parquet datasets, and ETL frameworks.
• Proven track record of owning mission-critical production systems at enterprise scale.

Nice to have

• Experience in retail measurement, consumer panel, or syndicated data domains.
• Experience with OmniShopper, Homescan, or similar consumer analytics platforms.
• Familiarity with modern data quality, governance, and observability frameworks.
• Experience working closely with Data Science and advanced analytics teams.

Culture & Benefits

• Flexible working environment.
• Volunteer time off.
• Access to LinkedIn Learning.
• Employee Assistance Program (EAP).