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

Global Sports Jobs Limited; Phoenix (AZ); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

A great place to work.

Fast-track growth opportunities.

Thoughtfully curated benefits and the…

Job summary

Warner Bros. Discovery is seeking an Engineering Manager to lead a small team of 2-5 engineers delivering Data & Audience Platform capabilities across data processing, self-service enablement, metadata, reliability and governance.

This frontline leadership role focuses on clarity, roadmap execution, and production-system reliability with cost awareness. As part of the DICE team, you will drive platform modernization, establish SLIs/SLOs, and collaborate with product, analytics and engineering

Qualifications

• Bachelor's degree or higher in CS, Engineering or related field.
• 12+ years of professional software or data engineering experience.
• 3+ years of direct management of engineers.
• Hands-on experience building and operating large-scale data platforms, distributed systems or cloud infrastructure.
• Strong understanding of batch and stream processing, data lakehouse architecture, metadata, governance, access control, orchestration, observability and cost management.
• Knowledge of distributed systems, cloud platforms, engineering operations and enterprise-grade governance.
• Proven ability to lead delivery of technical programmes 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.
• Strong written and verbal communication skills.

Responsibilities

• Lead a small team of 2-5 engineers delivering 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.
• Build a strong engineering team culture focused on ownership, customer impact, reliability, inclusion and high standards, coaching engineers to improve technical judgment, execution quality, stakeholder communication and operational discipline.
• Hire, develop and retain engineers, grow tech leads and emerging technical leaders, and regularly engage stakeholders to communicate status, risks and key decisions.
• Own the team's backlog and delivery roadmap, translating departmental goals into prioritised, well-scoped work matched to available engineering capacity.
• Modernise platform capabilities across storage, compute, orchestration, ingestion, access, metadata and self-service workflows, and partner with peer managers to align priorities and reduce duplication of effort.
• Establish and maintain strong operational practices across owned systems, including SLIs/SLOs, dashboards, alerts, runbooks, incident response, RCAs/COEs and post-incident learning, while improving alert quality, reducing manual toil and increasing automation.
• Drive a culture of proactive reliability engineering, cost-aware design and continuous improvement across platform operations.
• Drive adoption of metadata, lineage, ownership, classification, data quality, access review and lifecycle management practices, and improve the discoverability and trustworthiness of data assets through cataloguing, documentation, schema management and data product standards.
• Deliver self-service onboarding, automated access workflows, reusable templates and standard platform patterns that reduce manual engineering dependency and improve developer experience for teams building, deploying, operating and governing data products.
• Partner with engineering, product, program management, analytics, data science, operations engineering, security, governance, privacy and business stakeholders, embedding controls into platform workflows rather than treating them as manual afterthoughts.

Skills

Data platform engineering

Distributed systems

Cloud infrastructure

Leadership / people management

Roadmap & delivery

Operational excellence / SRE

Education

Bachelor's degree in Computer Science, Engineering or related field

Tools

Databricks

Snowflake

Kafka

Airflow

Kubernetes

AWS

Job description

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 role sits within the DICE (Data Insights, Collection & Engineering) team, which builds and operates a scalable, multi-tenant data ecosystem enabling analytics, real-time insights and machine learning across products such as Max, Discovery+, Sports, Studios and News. The team works at the intersection of data and platform engineering, building robust pipelines and ensuring data quality and governance, in close collaboration with product, analytics and engineering stakeholders.

Key Responsibilities

• Lead a small team of 2-5 engineers delivering 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.
• Build a strong engineering team culture focused on ownership, customer impact, reliability, inclusion and high standards, coaching engineers to improve technical judgment, execution quality, stakeholder communication and operational discipline.
• Hire, develop and retain engineers, grow tech leads and emerging technical leaders, and regularly engage stakeholders to communicate status, risks and key decisions.
• Own the team's backlog and delivery roadmap, translating departmental goals into prioritised, well-scoped work matched to available engineering capacity.
• Modernise platform capabilities across storage, compute, orchestration, ingestion, access, metadata and self-service workflows, and partner with peer managers to align priorities and reduce duplication of effort.
• Establish and maintain strong operational practices across owned systems, including SLIs/SLOs, dashboards, alerts, runbooks, incident response, RCAs/COEs and post-incident learning, while improving alert quality, reducing manual toil and increasing automation.
• Drive a culture of proactive reliability engineering, cost-aware design and continuous improvement across platform operations.
• Drive adoption of metadata, lineage, ownership, classification, data quality, access review and lifecycle management practices, and improve the discoverability and trustworthiness of data assets through cataloguing, documentation, schema management and data product standards.
• Deliver self-service onboarding, automated access workflows, reusable templates and standard platform patterns that reduce manual engineering dependency and improve developer experience for teams building, deploying, operating and governing data products.
• Partner with engineering, product, program management, analytics, data science, operations engineering, security, governance, privacy and business stakeholders, embedding controls into platform workflows rather than treating them as manual afterthoughts.

Required Experience & Qualifications

• 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.
• 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.
• Knowledge of distributed systems, cloud platforms, engineering operations and enterprise-grade governance.
• Proven ability to lead delivery of technical programmes 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.

Preferred Skills

• 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, catalogue, 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 organisation across India and United States time zones.

Workplace

• Team operates within a globally distributed organisation spanning India and United States time zones.

Benefits & Perks

• A great place to work.
• Fast-track growth opportunities.
• Thoughtfully curated benefits and the tools to explore and grow.

The Application Process

1. The company's guiding principles are discussed with candidates during the interview process.
2. Adjustments or accommodations during the job application and recruitment process are available on request for qualified candidates with a disability.