Are you ready to revolutionize the advertising industry? At Cognitiv, we are not just another AdTech company—we are industry trailblazers redefining media buying with our Deep Learning Advertising Platform. Since 2015, we have harnessed the power of cutting-edge deep learning technology and data science to transform how brands connect with their customers.

Our mission? To bring intelligence to advertising and deliver unparalleled precision, relevance, and impact at scale. With our innovative platform, advertisers enjoy unprecedented flexibility—whether it is activating Dynamic Deals through their preferred DSP, leveraging our managed service DSP, or utilizing our industry-first ContextGPT product.

As a part of Cognitiv, you will be at the forefront of AI-driven advertising solutions, driving change and achieving remarkable growth in a rapidly evolving industry. Now, we’re growing! The Role As a Senior Software Engineer, Big Data, you will own the design, delivery, and reliability of the core data systems powering our platform.

You will strengthen our data platform capabilities as we continue scaling our systems and AI-driven initiatives, serving as a central force in managing our data warehouse and driving large-scale data initiatives like ML feature projection. In this role, you will work across the full data lifecycle—building, optimizing, and scaling pipelines that power analytics, machine learning, and activation across billions of events and diverse data sources. Location: Our Vancouver office will open on September 1 in Mount Pleasant.

The Founding Engineering team will work remotely through the summer. Starting September 1, the role will transition to a hybrid model: in-office Monday-Wednesday, with remote flexibility on Thursday and Friday. Your Impact In this role, success is measured by the reliability, scalability, and performance of our data platform.

You will: Lead Technical Design: Own the end-to-end design and delivery of large-scale data ingestion, warehousing, and processing pipelines across billions of daily events—proactively accounting for scalability, failure modes, and security from the start. This includes core data workflows such as the identity graph, ML feature pipelines, and warehouse workload distribution. Elevate Reliability: Monitor, troubleshoot, and improve highly available data systems including low-latency data streams and distributed query workloads.

Lead blameless post-mortems and implement long-term systemic fixes to prevent incident recurrence. Drive Engineering Excellence: Write and optimize complex SQL and Spark queries, extend modern big data tooling (Spark, Flink, Kafka, Iceberg, ClickHouse, AWS EMR/S3), and strengthen the team through high-quality code reviews, technical mentorship, and exemplary technical artifacts such as design docs and architecture diagrams. Navigate Ambiguity: Exercise strong judgment to balance long-term data platform health with rapid development velocity—particularly when driving ML feature projection work across large datasets and solving cross-team issues quickly with a small, focused team.

Collaborate on Direction: Partner with Science, Machine Learning, Product, and Engineering leadership to align technical solutions with business priorities around AI-driven initiatives, including feature engineering, feature projections, and identity graph development.

Who You Are

Experienced Senior Engineer. NET, building production-grade systems. Deep Spark Practitioner.

You have extensive hands-on experience with Spark in production environments, including scaling large datasets in both Spark and SQL. Strong Backend Foundation. You have a proven track record designing, decomposing, and delivering high-scale production services or distributed systems.

Cloud-native engineer.