Hybrid Manager – Software Engineering, Data Core Processing

at Warner Bros. Discovery

• Job title: Manager – Software Engineering, Data Core Processing
• Job type: Full Time
• Experience level: Senior, Lead
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: Airflow, AWS, Azure, BigQuery, Cloud, Distributed Systems, Docker, ElasticSearch, Google Cloud Platform, Java, Kafka, Kubernetes, MongoDB, Postgres, Python, Redis, Scala, Spark, SQL, Terraform, Go
• Location requirements: Hybrid, Hyderabad, India

About the role

• Engineering Manager leading Data Core Processing team at Warner Bros. Discovery. Focusing on building enterprise-grade data platforms and ensuring operational excellence across distributed data systems.

Responsibilities

• Lead, mentor, and grow a team of 6–10 software and data engineers, fostering a culture of collaboration and engineering excellence
• Define and execute the technical roadmap for data processing infrastructure
• Design and build scalable data pipelines for structured, semi-structured, and unstructured data
• Develop systems supporting both real-time and batch data processing at scale
• Ensure data quality, reliability, and consistency across pipelines
• Optimize system performance and manage infrastructure costs effectively
• Oversee development of orchestration frameworks and data processing workflows
• Implement metadata management, data cataloging, and enrichment capabilities
• Establish monitoring, alerting, and observability frameworks for data systems
• Ensure compliance with data governance, privacy, and security standards
• Collaborate with Data Science, Analytics, Product, and Infrastructure teams to deliver high-impact solutions
• Define SLAs/SLOs and drive reliability and operational improvements
• Lead incident management, root cause analysis, and post-mortem processes
• Promote DevOps best practices, automation, and continuous improvement
• Manage technical debt while balancing feature development and platform stability

Requirements

• 8+ years of experience in data engineering, distributed systems, or related domains
• 3+ years of experience in engineering management leading technical teams
• Strong expertise in data processing frameworks such as Spark, Kafka, Flink, Airflow, Beam, or similar
• Proficiency in programming languages like Python, SQL, Java/Scala, or Go
• Hands-on experience with cloud platforms (AWS, GCP, or Azure) and their data services (e.g., EMR, Glue, Lambda, S3, BigQuery , Dataflow)
• Proven experience in building and scaling data infrastructure and platforms
• Experience with both batch and streaming data architectures
• Strong understanding of data modeling, schema design, and data warehousing concepts
• Experience with modern data storage formats and frameworks such as Parquet, Avro, Delta Lake, Iceberg, or Hudi
• Experience working with databases such as PostgreSQL, MongoDB, Elasticsearch, or Redis
• Experience with orchestration tools like Airflow, Prefect, Temporal, or Argo
• Familiarity with containerization and infrastructure tools such as Docker, Kubernetes, Terraform, and CI/CD pipelines
• Experience working with unstructured data (documents, images, video, audio) is a plus
• Knowledge of modern data stack, data lake architectures, and multi-tenant platforms
• Familiarity with AI/ML data pipelines, feature engineering, and data-driven applications
• Understanding of data quality frameworks, observability tools, and governance practices
• Exposure to vector databases and semantic search technologies is a plus
• Contributions to open-source data processing projects are a plus
• Excellent problem-solving, communication, and leadership skills.

Benefits

• Equal opportunity employer
• Fast-track growth opportunities