Sr. Computer Scientist (Data Platform Engineer)
Adobe · Bengaluru · 10+ yrs experience · Posted 2026-03-15
Tech stack: AWS, Azure, Cassandra, GCP, Java, Kafka, Scala
Apply on the company site · Get a referral for this role
Adobe salary & ratings · Adobe interview process · More live openings
About the role
About the Team The Adobe Advertising Data Engineering team powers data platforms that process billions of events every day, enabling real-time decisioning, analytics, and machine learning at scale. We operate with a strong engineering-first mindset, focusing on building highly reliable, scalable, and cost-efficient data systems. We foster a collaborative and innovation-driven culture, building self-service data platforms that empower teams across Adobe Advertising to unlock the full value of data. The Opportunity Are you passionate about solving data challenges at massive scale? We are looking for a Senior Computer Scientist to help design and build next-generation data platforms within Adobe Advertising. In this role, you will work on distributed systems that handle high-throughput, low-latency data processing. You will collaborate closely with cross-functional teams to enable robust data infrastructure that powers critical business decisions, customer experiences, and AI-driven products. Impact You’ll Make You will play a key role in building the data platform that drives Adobe Advertising’s core systems. Your work will enable scalable, high-performance pipelines that process massive data volumes with reliability and efficiency. By contributing to architectural improvements and engineering excellence, you will help enhance system robustness, optimize infrastructure costs, and accelerate data-driven and AI-powered capabilities. Key Responsibilities Design and build scalable, distributed data systems for real-time and batch processing Develop high-throughput data pipelines processing 10B+ events per day Contribute to and own key components in the technical design and implementation of core AdCloud platform components Work with technologies such as Apache Spark, Kafka, Hadoop ecosystem, and modern data platforms Ensure performance, scalability, reliability, and cost efficiency of data systems Collaborate with Product, Engineering, and Data Science teams to deliver end-to-end solutions Participate in design and code reviews to maintain high engineering standards Continuously improve system robustness, scalability, and developer productivity Qualifications 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
Qualifications
- 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
Responsibilities
- Design and build scalable, distributed data systems for real-time and batch processing
- Develop high-throughput data pipelines processing 10B+ events per day
- Contribute to and own key components in the technical design and implementation of core AdCloud platform components
- Work with technologies such as Apache Spark, Kafka, Hadoop ecosystem, and modern data platforms
- Ensure performance, scalability, reliability, and cost efficiency of data systems
- Collaborate with Product, Engineering, and Data Science teams to deliver end-to-end solutions
- Participate in design and code reviews to maintain high engineering standards
- Continuously improve system robustness, scalability, and developer productivity Qualifications 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