Senior Software Engineer, Attribution & Events
Cognitiv
| Company | Cognitiv |
| Category | Engineering |
| Location | Vancouver |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 29 May 2026 |
| Last verified | 3 Aug 2026 |
| Source | Employer career page (greenhouse) |
Description
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 on the Attribution & Events team, you will be the driving force behind the platform that proves campaign performance. You will own the design, delivery, and reliability of high-stakes data systems that solve the hardest cross-device identity challenges, surgically linking purchases with customers who saw an ad. This mission is absolutely critical to the performance of our ML and overall campaign effectiveness. Get ready to master data at an epic scale, managing datasets with billions of records and trillions of data points across identity resolution, attribution, incrementality measurement, and campaign management.
This role is heavily weighted toward big data engineering, analytical SQL, and OLAP systems (primarily ClickHouse), with backend service work in C# / .NET and Java to operationalize the data products you build.
You'll navigate ambiguity and make the critical tradeoffs that drive system performance and engineering effectiveness — and you'll do it as part of the founding Vancouver engineering team, helping us set the technical bar and shape the culture of a new hub from day one.
Your Impact
In this role, success is measured by the reliability, scalability, and performance of our event data platform. You will:
Lead Technical Design: Own end-to-end delivery of high-volume data services — from ClickHouse schema and partitioning to ingestion pipelines to the C# services on top — accounting for scalability, failure modes, and cost up front.
Build & Scale the Data Backbone: Architect ClickHouse-backed pipelines that ingest, store, and query billions of ad events (impressions, conversions, identity signals). Own loaders, partitioning, materialized views, and query optimization end-to-end.
Operationalize via Backend Services: Build C# / .NET Core 8 services that power attribution, incrementality measurement, and campaign management on top of the data layer.
Integrate Identity & Event Sources: Ingest events from LiveRamp, pixels, CTV, and IP-based signals; integrate identity graphs and resolve cross-vendor IDs at scale.
Elevate Reliability: Identify bottlenecks across the data path, improve observability (ingestion lag, query latency, data quality), lead blameless post-mortems, and implement long-term systemic fixes.
Drive Engineering Excellence: Strengthen the team through high-quality code and SQL reviews, mentorship, and strong design docs, data models, and query patterns.
Navigate Ambiguity: Make strong calls on the open questions, balancing long-term data architecture health with development velocity.
Collaborate on Direction: Partner with Product, Science, and Engineering to align technical work with measurement and business priorities.
Required Experience & Capabilities
Big Data & OLAP : Deep hands-on experience with a columnar/OLAP store (ClickHouse strongly preferred; Snowflake, BigQuery, Redshift, or other petabyte scale big data experience acceptable). Exper
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