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

For more information, please visitwww.wbd.com

Meet OurTeam:

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 andoperatesa scalable, multi-tenant data ecosystem that enables analytics, real-time insights, and machine learningusecases across the organization. Positioned at the core of the data journey, the teamis responsible foringesting, 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 atscale.

About theRole:

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, andoperateproduction 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 mustretainenough 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, andhigh standards.

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

Hire, develop, andretainengineers 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 andmaintainstrong operational practices across owned systems, including SLIs/SLOs, dashboards, alerts, runbooks, incidentresponse, 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, andcostguardrails.

What to Bring:

ABachelor’sdegree or higher in Computer Science, Engineering, ora relatedfield.

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 andoperatinglarge-scale data platforms, distributed systems, or cloud infrastructure, with a strong understanding of modern data platform concepts such as batch and stream processing, datalakehousearchitecture, 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 toHave:

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 asDataHub, 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 developinga teamwithin 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

How We Get Things Done…

This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview.

Championing Inclusion at WBD

Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, regardless of sex, gender identity, ethnicity, age, sexual orientation, religion or belief, marital status, pregnancy, parenthood, disability or any other category protected by law.

If you’re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.