Principal Engineer, Architecture — Audiences & Measurement

Drive architectural convergence between audiences/segments and measurement so they function as one cohesive system

• Help define our technical approach to data clean room integrations, as measurement partnerships increasingly require privacy-safe data collaboration

Help define our technical approach to data clean room integrations, as measurement partnerships increasingly require privacy-safe data collaboration

• Act as a technical thought partner to engineering leadership, raising the bar on design rigor, code quality, and operational excellence

Act as a technical thought partner to engineering leadership, raising the bar on design rigor, code quality, and operational excellence

• Mentor senior and staff-level engineers, and drive alignment on architecture across teams that own adjacent parts of the measurement/audiences stack

Mentor senior and staff-level engineers, and drive alignment on architecture across teams that own adjacent parts of the measurement/audiences stack

• Identify and de-risk technical debt, scalability bottlenecks, and single points of failure before they become organizational blockers

Identify and de-risk technical debt, scalability bottlenecks, and single points of failure before they become organizational blockers

• Extensive experience architecting large-scale, data-intensive systems (streaming/batch pipelines, distributed data stores, or audience/measurement platforms)

Extensive experience architecting large-scale, data-intensive systems (streaming/batch pipelines, distributed data stores, or audience/measurement platforms)

• A track record of technical leadership at scale without direct reports — driving alignment across teams through influence and design rigor

A track record of technical leadership at scale without direct reports — driving alignment across teams through influence and design rigor

• Strong system design fundamentals: data modeling, distributed systems tradeoffs, scalability and reliability patterns

Strong system design fundamentals: data modeling, distributed systems tradeoffs, scalability and reliability patterns

• Strong cross-functional communication skills, with experience partnering across product, data science, and multiple engineering teams

Strong cross-functional communication skills, with experience partnering across product, data science, and multiple engineering teams

• Comfortable operating with significant ambiguity and defining technical direction where none currently exists

Comfortable operating with significant ambiguity and defining technical direction where none currently exists

• Ad tech or adjacent industry experience

Ad tech or adjacent industry experience

• Experience with data clean rooms — clean room-based collaboration is an area we expect to grow significantly within measurement

Experience with data clean rooms — clean room-based collaboration is an area we expect to grow significantly within measurement

• Background working across multiple time zones or with globally distributed engineering teams .

Background working across multiple time zones or with globally distributed engineering teams .