Senior Software Engineer - Data Engineering ( Adtech Team),Bangalore

We focus on all aspects of streaming video: live and VOD pipelines, metadata transformation, ad tech, server-side ad insertion, CDN integrations, playback services, video player backends, and AI/ML-based personalization. You will play a critical role in expanding and optimizing our data and reporting capabilities. You will work on the development of a scalable, high-impact data systems powering reporting and analytics for our advertising business This is a multi-faceted role requiring expertise in backend service development, streaming and batch services, and operational excellence. Design architecture and development of high-scale data pipelines and backend services for forecasting, reach reports, and advertiser analytics. Work closely with product teams to understand reporting needs and translate them into reliable, performant systems. Design and implement batch and real-time processing pipelines using modern big data tools (e.g., Spark, Flink, Kafka, Airflow). Drive data modeling best practices to ensure consistent, extensible data definitions across the organization. Ensure data quality, correctness, and completeness through robust monitoring, validation, and testing strategies. Mentor junior engineers, foster engineering excellence, and help shape technical direction across the broader organization. Partner with infrastructure and platform teams to ensure systems are cost-efficient, observable, and resilient at scale. Develop and enforce data engineering, security, data quality standards through automation. Participate in supporting platform 24X7. Be passionate about growing a team - hire and mentor engineers . Bachelor’s degree in computer science or similar discipline . 5 - 8 years of experience in software engineering, with a strong background in data-intensive systems . Deep experience with distributed data processing frameworks (e.g., AWS Kinesis, Flink). Proficiency in two or more programming languages such as Java, Python, or Go. Strong understanding of data modelling, ETL best practices, and big data architecture. Experience building reporting pipelines or systems that support forecasting, attribution, reach/frequency, or audience measurement. Exposure to ML-based forecasting systems or time-series modelling. Expertise in building and managing large volume stream or batch processing platform is a must. Experience working with data warehousing solutions like Databricks. Practical knowledge of with CI/CD pipelines, preferably GitHub Actions Workflows. Experience with Microservice Architecture principles and implementations. Practical knowledge of containerization and orchestration platforms like Docker and EKS. Experience with cloud services, especially AWS, is highly desirable. Strong interpersonal, communication and presentation skills. What You’ll Do. Championing Inclusion at WBD.