Sr. Computer Scientist (data Platform Engineer)

Adobe Adobe · Enterprise · Bangalore, India

This role is for a Senior Computer Scientist on the Adobe Advertising Data Engineering team. The primary focus is on designing and building next-generation data platforms that process billions of events daily, enabling real-time decisioning, analytics, and machine learning at scale. The role involves working with distributed systems, high-throughput data pipelines, and ensuring the performance, scalability, reliability, and cost efficiency of these data systems. While the role supports AI/ML initiatives, its core craft is data engineering and platform development, not direct AI/ML model building.

What you'd actually do

  1. Design and build scalable, distributed data systems for real-time and batch processing
  2. Develop high-throughput data pipelines processing 10B+ events per day
  3. Contribute to and own key components in the technical design and implementation of core AdCloud platform components
  4. Work with technologies such as Apache Spark, Kafka, Hadoop ecosystem, and modern data platforms
  5. Ensure performance, scalability, reliability, and cost efficiency of data systems

Skills

Required

  • 10+ years of experience in designing and developing large-scale data-driven systems
  • Strong experience with distributed data processing frameworks (Spark, Kafka, Hadoop, etc.)
  • Experience with NoSQL systems (HBase, Aerospike, Cassandra) and RDBMS
  • Strong programming skills in Java, Scala, or similar languages
  • Solid understanding of data structures, algorithms, and system design
  • Experience building scalable systems on cloud platforms (AWS/GCP/Azure)
  • Strong focus on performance optimization and cost efficiency
  • Excellent communication and collaboration skills

Nice to have

  • Experience in AdTech or high-scale event-driven systems
  • Exposure to data governance, data quality, and metadata systems
  • Experience supporting ML/AI data pipelines
  • Familiarity with modern data architectures (data lakes, lakehouse, etc.)
  • Contributions to open-source or technical communities