Senior / Staff Data Engineer (AdTech)

TL;DR

Senior / Staff Data Engineer (Spark/Kafka): Building and evolving the data processing and pipeline layer for reporting and billing systems with an accent on large-scale batch and streaming architectures. Focus on optimizing processing efficiency, managing data correctness at scale, and evolving legacy Hadoop systems toward distributed patterns.

Location: Hybrid in Toronto. Must be open to working in the office on Tuesdays, Wednesdays, and Thursdays.

Company

A global advertising supply-side platform processing over 550 billion real-time auctions daily to empower media owners and marketers.

What you will do

• Design and operate batch and streaming pipelines using Spark, Kafka, and Flink.
• Transform raw event data into production-grade cleaned and business-ready datasets.
• Build and maintain Airflow DAGs for pipeline scheduling, dependency management, and backfills.
• Optimize pipelines for performance, compute cost efficiency, and scalability.
• Define and evolve data processing standards and architecture patterns across the organization.
• Collaborate with API, Data Platform, and ML teams to support reporting, billing, and experimentation.

Requirements

• Strong experience in data engineering at scale.
• Deep expertise in Spark and SQL/data modeling.
• Experience with Airflow or similar workflow orchestration tools.
• Experience with Kafka or other streaming systems.
• Strong understanding of distributed data processing and performance optimization.
• Ability to own pipelines end-to-end and debug complex data issues in high-scale environments.

Culture & Benefits

• Comprehensive health, dental, and vision plans for employees and dependents.
• Paid time off, health days, personal obligation days, and flexible work schedules.
• Competitive retirement matching plans and equity packages.
• Generous parental leave for birthing, non-birthing, and adoptive parents.
• Annual well-being allowance, fitness discounts, and mental health support programs.
• Commuter benefits and opportunities for continuous learning.