Responsibilities
Lead architecture and technical roadmap execution for scalable systems supporting off-platform advertising, cleanrooms, taxonomy automation, and the Ads Data Solutions Platform.
Build and expand external advertising integrations, privacy-forward activation and identity workflows, and measurement ingestion pipelines.
Extend cleanroom orchestration and governance tooling, including multi-cleanroom support, policy enforcement, reusable query templates, and partner configurations.
Lead taxonomy intake automation and release workflow improvements across UI and backend systems.
Modernize platform foundations, developer tooling, testing, observability, cost efficiency, and operational practices including on-call and SLO strategy.
Use AI-assisted tools for design, coding, testing, documentation, internal automation, and team workflow development.
Mentor engineers up to L5, establish engineering standards, and drive cross-team collaboration with Product, Data Science, Data Platform, Governance, Privacy/Legal, and external partners.
Requirements
8+ years of software engineering experience delivering and operating large-scale backend and data systems, with cross-team project and architectural leadership.
Strong Python skills and proficiency in either Ruby or Go, including services, APIs, and third-party API integrations.
Experience building data pipelines with DBT and Airflow, using Spark or Databricks, writing advanced SQL, and performing performance tuning.
Experience with Snowflake, AWS, workflow orchestration such as Temporal, and event-driven system patterns.
Experience with ad-tech or programmatic advertising, measurement integrations, cleanrooms, identity and matching systems, and data deconfliction.
Working knowledge of GDPR and CCPA privacy and compliance practices in data workflows.
Experience with CI/CD, containers, testing strategy, observability, incident readiness, and SLO-oriented operations.
Recent hands-on experience with AI-assisted development tools, reusable prompts and workflows, AI-enabled internal tools or automation, and AI evaluation, guardrails, and security and privacy considerations.
Strong technical writing, stakeholder management, consensus-building, and execution skills.
Preferred qualifications include UID2 or TTD integrations; Roku, PubMatic, NBCUniversal, Meta Advanced Analytics, or Google ADH pipelines; catalog or taxonomy systems; Snowflake governance; partner data collaboration; vendor management; and AI-powered internal tools.
Benefits
Flex First remote work arrangement allowing employees to work from home, an office, or another preferred location, with regular in-person events.
Occasional travel to the Toronto office to connect with the broader engineering community.
Eligibility for a new hire equity grant and annual refresh grants.
Market-competitive location-dependent compensation and benefits.
