Engineering Manager (Data & Distributed Systems) - Data Platform , Hyderabad

Manager, Software Engineering – Data Platform, Hyderabad

About Warner Bros. Discovery :

Warner Bros. Discovery's Global Technology organization sits at the intersection of technology, entertainment, and everyday utility. Our platform powers experiences across streaming, content delivery, personalization, subscriptions, commerce, and analytics for millions of customers worldwide. As a technology organization, we build scalable, data-driven products that enable Warner Bros. Discovery's continued growth and support our streaming platforms.

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Meet Our Team:

The DICE (Data Insights, Collection & Engineering) team at Warner Bros. Discovery powers data-driven experiences across global products like Max, Discovery+, Sports, Studios, and News. The team builds and operates a scalable, multi-tenant data ecosystem that enables analytics, real-time insights, and machine learning use cases across the organization. Positioned at the core of the data journey, the team is responsible for ingesting, processing, and transforming large volumes of client and server-side data into reliable and high-quality datasets. Operating at the intersection of data and platform engineering, the team focuses on building robust pipelines, ensuring data quality and governance, and driving innovation in real-time processing, observability, and modern data infrastructure. The team collaborates closely with product, analytics, and engineering stakeholders to enable data-driven decision-making at scale.

About the Role:

Warner Bros. Discovery is looking for an Engineering Manager to lead a small team of 2-5 engineers delivering critical Data & Audience Platform capabilities across data processing, self-service enablement, metadata, reliability, and operational excellence. This is a frontline engineering leadership role for a manager who can create clarity for a small team, drive execution discipline against a clear roadmap, and operate production systems with strong reliability and cost awareness.

The candidate must be well versed in modern data platform concepts, distributed systems, cloud platforms, engineering operations, and enterprise-grade governance, and must retain enough hands-on depth to review designs and guide the team’s technical decisions.

Role Scope

• Lead a small team of 2-5 engineers responsible for foundational Data & Audience Platform capabilities used across analytics, data engineering, business intelligence, operational workflows, and AI/ML enablement.

• Own execution across data collection, batch and streaming data processing, metadata, observability, cost efficiency, and self-service platform capabilities within the team’s domain.

• Partner closely with engineering, product, program management, analytics, data science, operations engineering, security, and business stakeholders.

Roles & Responsibilities:

Engineering Leadership

• Build a strong engineering team culture focused on ownership, customer impact, reliability, inclusion, and high standards.

• Coach engineers to improve technical judgment, execution quality, stakeholder communication, and operational discipline.

• Hire, develop, and retain engineers on the team, and grow tech leads and emerging technical leaders.

• Regularly engage stakeholders to communicate status, risks, and key decisions for the team’s space.

Delivery and Execution

• Own the team’s backlog and delivery roadmap, translating departmental goals into prioritized, well-scoped work matched to available engineering capacity.

• Modernize platform capabilities across storage, compute, orchestration, ingestion, access, metadata, and self-service workflows within the team’s scope.

• Partner with peer managers to align priorities across overlapping platform workstreams and reduce duplication of effort.

Operational Excellence

• Establish and maintain strong operational practices across owned systems, including SLIs/SLOs, dashboards, alerts, runbooks, incident response, RCAs/COEs, and post-incident learning.

• Improve alert quality, reduce manual toil, and increase automation across platform operations.

• Drive a culture of proactive reliability engineering, cost-aware design, and continuous improvement.

Governance, Metadata, and Data Trust

• Drive adoption of metadata, lineage, ownership, classification, data quality, access review, and lifecycle management practices.

• Improve the discoverability and trustworthiness of data assets through cataloging, documentation, schema management, and data product standards.

• Partner with governance, privacy, and security stakeholders to embed controls into platform workflows rather than treating them as manual afterthoughts.

Self-Service and Developer Experience

• Deliver initiatives that reduce manual engineering dependency through self-service onboarding, automated access workflows, reusable templates, and standard platform patterns.

• Improve developer experience for teams building, deploying, operating, and governing data products.

• Apply consistent platform standards that help teams move faster while staying within reliability, privacy, security, and cost guardrails.

What to Bring:

• A Bachelor’s degree or higher in Computer Science, Engineering, or a related field.

• 12+ years of professional software or data engineering experience.

• 3+ years of experience directly managing engineers, including hiring, performance management, and career development.

• Hands-on experience building and operating large-scale data platforms, distributed systems, or cloud infrastructure, with a strong understanding of modern data platform concepts such as batch and stream processing, data lakehouse architecture, metadata, governance, access control, orchestration, observability, and cost management.

• Proven ability to lead delivery of technical programs across multiple stakeholders.

• Strong operational excellence mindset, including incident management, monitoring, SLOs, runbooks, RCA/COE practices, and production readiness.

• Experience driving automation, developer productivity, and scalable engineering workflows.

• Sufficient hands-on depth to review designs and code and make sound technical trade-offs, without needing to be the deepest expert in every technology.

• Strong written and verbal communication skills, with the ability to simplify complex topics for leadership and cross-functional partners.

Good to Have:

• Experience with large-scale data platforms using technologies such as Databricks, Snowflake, Apache Flink, Kafka, Airflow, Apache Iceberg, Spark, Kubernetes, AWS, or similar platforms.

• Experience with metadata, catalog, lineage, governance, and data quality platforms such as DataHub, Unity Catalog, Monte Carlo, or similar tools.

• Exposure to AI/ML or GenAI platform enablement, including governance, observability, model or prompt lifecycle, or data readiness for AI use cases.

• Experience supporting data products, semantic layers, data certification, and self-service onboarding.

• Experience working in media, streaming, advertising, consumer product, or high-scale digital platform environments.

• Experience leading and developing a team within a globally distributed organization across India and United States time zones.

What We Offer:

• A Great Place to work

• Equal opportunity employer

• Fast track growth opportunities