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Job Description
Structured overview of role & requirementsAbout This Role
Design and develop large-scale backend services, APIs, and microservices for high-throughput data and advertising systems.
Build and maintain real-time and batch data pipelines using Apache Spark, Kafka, Flink, and ensure performance and reliability in distributed systems with low-latency data processing.
Lead architectural decisions, mentor juniors, collaborate cross-functionally to deliver scalable, AI-powered engineering solutions for an omni-channel advertising exchange.
Minimum Requirements
5–8 years of backend engineering experience, preferably in large-scale, high-traffic environments.
Strong programming skills in Java, Scala, or Go; Python familiarity is a plus for data use cases.
Experience with data infrastructure tools such as Spark, Kafka, Airflow, Databricks, Presto, ClickHouse.
Exposure to cloud-native architecture (GCP/Azure) and containerization (Kubernetes, Docker).
Ideal Candidate Profile
Experienced in building and scaling distributed, large-scale data and advertising backend systems with emphasis on reliability and performance.
Comfortable operating at the intersection of AI, large-scale systems, and ad tech, and capable of driving architectural and technical strategy.
Able to lead technical discussions and mentor teams, working collaboratively across product, data science, and engineering functions.