Our main Engineering challenges at Teads

• Build efficient and easy-to-use web products used by thousands of users working for the world’s most premium publishers, advertisers, and agencies.
• Rich and diverse tech stack and system architecture to optimize for performance, scalability, resiliency, and cost efficiency. We use mostly Scala and TypeScript, among others.
• Working in a very high-traffic environment (2.2 billion users per month, 100 billion events per day) with low latency and high availability constraints (2 million requests per second, responses in less than 150 milliseconds).
• Management of large datasets with milliseconds order of magnitude access time, to compute in a near real-time complex auction resolution algorithm (18 million predictions per second).
• A fast-changing environment where we continuously collaborate with Product teams and constantly adapt our Cloud infrastructure for new features and Products.
• Bring a wide diversity of profiles to the same level of quality and knowledge
• Work in an international environment with offices located in Israel, Slovenia and France.

Team Overview 

The Data Solution pod is the technical unit within Innovation responsible for leveraging Teads'publisher integrations and network scale to provide targeting solutions and measurable business outcomes. We build the infrastructure that unifies fragmented signals from the "Open Internet" into actionable data about the customer journey for our SSPs and internal Buying Engines.

The team is a senior-heavy center of expertise handling high-scale production delivery across three strategic pillars:

• Identity: The foundation linking user journeys across Mobile, Desktop, and CTV.
• Measurement: The full-stack engine proving outcomes (Attention, Sales Uplift, Brand uplift).
• Targeting: The segmentation and planning system for audience activation in a cross screen environment and cross buying engines. 

Key Responsibilities

Identity

Manage the identity graph at scale, interpreting data across the 30% deterministic / 30% interpreted / 40% probabilistic split.

• Evolve service-identity (Scala, C*) and oversee the production delivery of identity signals to the rest of the stack.
• Maintain privacy libraries and services to adapt signal ingestion to regional laws (GDPR, US, Asia) and browser restrictions.
• Leverage BigQuery/DBT and Python/Airflow for signal analysis and exploratory technical tooling.

Measurement

• Build the full-stack infrastructure for premium metrics (Attention, Brand Lift, Sales Uplift).
• Develop ETLs and integrate Data Science logic to transform raw signals into actionable reporting.
• Design and implement internal/external APIs to facilitate third-party feedback loops with measurement providers.
• Create high-performance dashboards and tools in TAM to show delivered outcomes. 

Targeting

• Develop/improve systems for user segmentation and cookieless data ingestion, ensuring multi-screen consistency.
• Build planning engines using BigQuery or other SQL technology to estimate reach, frequency, and ad opportunities volume.
• Deep integration with delivery services: as for example service-dmp (segment management) or lib-tbl (real-time rule resolution) and their future implementation in multivac and in the bidder.
• Ensure targeting rules are correctly propagated to internal Backends and external DSP/SSP integrations.

 

We care about you:

• Career Development: Continuous investment in our employees’ skills: in-house and external training, internal mobility 
• Life Balance: A well-balanced work-life for our employees is one of our top priorities: 22 days off per year, 15 days per year of work from anywhere, hybrid work (3 days per week in the office)
• Wellness: Prioritizing employee well-being through premium work equipment, enjoyable work environment (work-life balance, team building events, summits), work from home subsidy, promoting Diversity & Inclusion with internal & external initiatives, etc. 

 

Please submit your CV in English.