Manager – Software Engineering, Data Core Processing
Warner Bros. Discovery
full-time
Posted on:
Location Type: Hybrid
Location: Hyderabad • India
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Tech Stack
About the role
- 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
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
data engineeringdistributed systemsdata processing frameworksSparkKafkaFlinkAirflowPythonSQLAWS
Soft Skills
leadershipcommunicationproblem-solvingcollaborationmentoringincident managementroot cause analysiscontinuous improvementengineering excellenceoperational improvements