Live opening · Posted 27 days ago
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About the role
Description supplied by the original job listing.
We are seeking a highly motivated Senior Software Engineer to join the Ad Signals team. This team is responsible for developing robust platforms and integrations that facilitate critical Marketing, Data Engineering, and Fraud Detection initiatives. Key responsibilities include managing services that transmit user activity data in a privacy-safe approach to advertising partners, thereby ensuring precise ad targeting.
Responsibilities:
Additionally, the team oversees services for tracking performance data downloads and marketing campaign information, which are instrumental in enhancing our data science models.
Build event-driven systems using Kafka, PubSub and real-time data streams, powering automated messaging, feedback loops, and decisioning workflows.
Develop and maintain scalable RESTful APIs and Spring Boot-based microservices, enabling integration across marketing automation systems, customer data pipelines, and external vendors.
Enhance platform reliability and observability by building monitoring dashboards, SLA enforcement metrics, and automated anomaly detection for throughput, latency, and deliverability.
Collaborate cross-functionally with Product, Data Science, and Marketing to define requirements, ensure system interoperability, and drive measurable impact in engagement and conversion.
Raise technical excellence by promoting best practices in backend architecture, distributed system design, API lifecycle management, and continuous integration/deployment.
Requirements:
Bachelor's or Master's degree in Computer Science, Software Engineering, or related technical discipline.
11+ years of experience building high-scale backend platforms and APIs for data-intensive or event-driven systems.
Strong command of Java (Spring Boot) and good working knowledge of Python, with a deep understanding of object-oriented design, concurrency, and multithreaded programming.
Strong command of stream processing frameworks (Flink, Spark Streaming) or Pub/Sub architectures.
Expertise in Kafka (topics, partitions, consumer groups, schema management) and event-driven microservices design.
Proven experience developing RESTful APIs and microservices with Spring Boot, including authentication, routing, and observability integration.
Strong background in cloud-native application design, deploying and managing workloads on GCP, AWS, or Azure, leveraging Docker and Kubernetes for containerization.
Solid foundation in data modelling, SQL/NoSQL databases, and high-performance data access patterns.
Strong problem-solving, debugging, and optimisation skills with an emphasis on scalability, fault tolerance, and SLA-driven reliability.
Familiarity with observability tools (Datadog, Grafana) and distributed tracing for root-cause analysis.
Ability to mentor engineers, perform design/code reviews, and lead technical discussions across multiple workstreams.
Excellent communication and collaboration abilities across engineering, product, and analytics teams.
Experience with LLM or GenAI applications (e. g., prompt orchestration, ranking pipelines, or creative optimisation systems).
Knowledge of A/B testing infrastructure, experimentation frameworks, and message-governance pipelines.
Background in config-driven workflow automation, feature flagging, or API gateway management.
Experience
11-15 yrs
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