SDE- Data Platform

About us :

Media.net is a leading, global ad tech company that focuses on creating the most transparent and efficient path for advertiser budgets to become publisher revenue. Our proprietary contextual technology is at the forefront of enhancing programmatic buying–, THE industry standard in ad buying across digital platforms.

The Media.net platform powers major global publishers and ad-tech businesses at scale across ad formats like display, video, mobile, native, as well as search. Media.net’s U.S. HQ is based in New York, and the Global HQ is in Dubai. With office locations and consultant partners across the world, Media.net takes pride in the value-add it offers to its 50+ demand and 21K+ publisher partners, in terms of both products and services.

Media.net in 1 year

125B+ ads served

17M+ URLs monetized

1B+ ad clicks managed

6T+ ad impressions delivered

About the Team :

As part of the Data Platform team at Media.net, you will contribute to building and scaling data infrastructure that processes billions of events daily. You’ll work on distributed systems, real-time data pipelines, and analytics frameworks that power our contextual advertising platform.

This role offers a great opportunity to work alongside experienced engineers, solve complex problems, and build high-performance systems on a scale.

What is in it for You?

Design, develop, and operate distributed systems for large-scale data ingestion, processing, and delivery.

Build and evolve core platform components on Kafka, Flink, and Spark to handle scale and reliability challenges.

Develop platform services and frameworks in Java, Go, and Python.

Participate in design discussions, code reviews, and performance tuning sessions.

Collaborate with cross-functional teams to deliver end-to-end data solutions.

Continuously learn and apply best practices in distributed systems, scalability, and reliability.

Who Should Apply for this Role?

1–3 years of experience in software development, preferably in backend or data-intensive systems.

Strong programming skills in Java or Go.

Good understanding of OOP, data structures, algorithms, and design principles.

Exposure to Big Data frameworks such as Hadoop, Spark, MapReduce, Kafka, HBase, or similar.

Strong analytical and problem-solving skills.

Eagerness to learn and work on large-scale distributed systems.

Strong communication and collaboration skills.