Senior Manager - Software Engineering- Data Platform

Warner Bros Discovery Warner Bros Discovery · Media · Hyderabad, Telangāna, India · Technology

Senior Manager for Data Platform Engineering to lead the design, development, and scaling of Warner Bros. Discovery’s data platform. This role involves owning the end-to-end architecture, collaborating with engineering teams, developing foundational tools, and ensuring platform availability and cost-effectiveness. The role also includes leading teams, partnering with cross-functional stakeholders, and driving operational excellence. While AI/ML and Generative AI are mentioned as ways to improve platform efficiency, the core focus is on data platform engineering.

What you'd actually do

  1. Own the end-to-end architecture of the data platform, ensuring scalability, efficiency, security, and governance
  2. Collaborate with engineering teams to design and build cost-effective and high-performing platform solutions
  3. Develop foundational tools and frameworks to enhance data processing, governance, and data quality
  4. Drive adoption of best practices aligned with open-source standards and contribute to engineering communities
  5. Leverage AI/ML and Generative AI techniques to improve platform efficiency and data workflows

Skills

Required

  • Java
  • Python
  • C++
  • Distributed systems
  • Spark
  • Kafka
  • Airflow
  • Kubernetes
  • Databricks
  • Snowflake
  • AWS
  • Data lakes
  • Data engineering
  • Infrastructure as code
  • Terraform
  • CI/CD
  • Docker
  • EKS
  • PostgreSQL
  • Elasticsearch
  • Cloud security
  • Leadership
  • Stakeholder management

Nice to have

  • GitHub Actions
  • Looker
  • Tableau
  • Generative AI use cases in data engineering
  • Scalable, multi-tenant data platforms

What the JD emphasized

  • 14+ years of experience delivering complex software engineering systems and platforms
  • Strong programming experience in Java, Python, C++, or similar languages
  • Hands-on experience with distributed systems and frameworks such as Spark, Kafka, Airflow, Kubernetes, Databricks, Snowflake, or similar
  • Experience with cloud platforms (AWS preferred) and modern data infrastructure
  • Strong understanding of data platforms, data lakes, and data engineering best practices
  • Experience with infrastructure as code (Terraform) and CI/CD pipelines (GitHub Actions preferred)
  • Experience with containerization technologies such as Docker and Kubernetes (EKS)
  • Knowledge of databases and storage systems like Snowflake, PostgreSQL, Elasticsearch
  • Experience in building AI/ML-driven platforms
  • Exposure to Generative AI use cases in data engineering