Über diese Principal Engineer, Architecture — Audiences & Measurement Stelle bei Sambatv
Sambatv · Vor Ort · Austin, Texas
Samba is a media intelligence company. We know what the world is watching, reading, and thinking about — in real time, at scale, across every screen. Our data exists with the consent of over a billion people, organized into the most complete picture of consumer attention ever built. The biggest brands in the world use that picture to make smarter decisions. We think it’s the most interesting data asset on the planet, because it’s the most culturally relevant.
Samba TV's Product Engineering team builds the software that puts our data to work — customer-facing platforms, internal tooling, and the APIs and services that connect them. Our engineers own meaningful systems end-to-end, ship production code every week, and work directly with product, data science, and go-to-market teams to deliver outcomes that matter.
As a Principal Engineer, you will own architecture and system design across our Audiences and Measurement product lines. These two systems currently evolve somewhat independently, and this role exists to bring them into architectural alignment — shared data models, consistent pipelines, and a unified approach to how we ingest, process, and activate viewership and audience data at scale. You'll set technical direction across teams rather than within one, and act as a thought partner to engineering leadership on the hardest design problems we have.
WHAT YOU'LL DO
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Set architectural direction and technical standards across measurement and audience systems, ensuring they scale reliably and remain extensible as new data sources and products come online
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Lead system design for high-impact, cross-team initiatives, balancing near-term delivery with long-term platform health
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Drive architectural convergence between audiences/segments and measurement so they function as one cohesive system
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Help define our technical approach to data clean room integrations, as measurement partnerships increasingly require privacy-safe data collaboration
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Act as a technical thought partner to engineering leadership, raising the bar on design rigor, code quality, and operational excellence
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Mentor senior and staff-level engineers, and drive alignment on architecture across teams that own adjacent parts of the measurement/audiences stack
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Identify and de-risk technical debt, scalability bottlenecks, and single points of failure before they become organizational blockers
WHO YOU ARE
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Extensive experience architecting large-scale, data-intensive systems (streaming/batch pipelines, distributed data stores, or audience/measurement platforms)
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A track record of technical leadership at scale without direct reports — driving alignment across teams through influence and design rigor
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Strong system design fundamentals: data modeling, distributed systems tradeoffs, scalability and reliability patterns
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Strong cross-functional communication skills, with experience partnering across product, data science, and multiple engineering teams
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Comfortable operating with significant ambiguity and defining technical direction where none currently exists
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Ad tech or adjacent industry experience
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Experience with data clean rooms — clean room-based collaboration is an area we expect to grow significantly within measurement
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Background working across multiple time zones or with globally distributed engineering teams.
Samba is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We strive to empower connection with one another, reflect the communities we serve, and tackle meaningful projects that make a real impact.
Samba may collect personal information directly from you, as a job applicant, Samba may also receive personal information from third parties, for example, in connection with a background, employment or reference check, in accordance with the applicable law. For further details, please see Samba's Applicant Privacy Policy. For residents of the EU , Samba Inc. is the data controller.
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