Staff Analytics Engineer

Welcome to Warner Bros. Discovery the stuff dreams are made of.

Who We Are

When we say the stuff dreams are made of were not just referring to the world of wizards dragons and superheroes or even to the wonders of Planet Earth. Behind WBDs vast portfolio of iconic content and beloved brands are the storytellers bringing our characters to life the creators bringing them to your living rooms and the dreamers creating whats next

From brilliant creatives to technology trailblazers across the globe WBD offers career defining opportunities thoughtfully curated benefits and the tools to explore and grow into your best selves. Here you are supported here you are celebrated here you can thrive.

Staff Software Engineer GVP QoE Platform Bangalore

About Warner Bros. Discovery:

Warner Bros. Discovery a premier global media and entertainment company offers audiences the worlds most differentiated and complete portfolio of content brands and franchises across television film streaming and gaming. The new company combines Warner Medias premium entertainment sports and news assets with Warner Bros Discoverys leading non-fiction and international entertainment and sports businesses.

For more information please visit

Meet Our Team:

The Video Playback organizations mission is to provide global self-service multi-tenant turn key solutions for all WBD Streaming brands both at Server and Client side across Live linear Live event & VOD stream types and wide array of device platforms serving all customers with seamless & smooth playback experience.

OurmissionistofosterunifiedQoE analytics and drive data driven use cases by leveraging a robust multitenant platform and semantic layer. We are committed to delivering innovative solutions that empower teams across the company to catalyze the video playback experience. We are obsessed with customer first mindset and providing them the excellent playback experience.

Roles & Responsibilities:

As aStaff Engineer you will lead data platform and pipeline data strategy and data visualization-related efforts. Youre an engineer who not only understands how to use big data in answering complex business questions but also how to design semantic layers to best support self-service vehicles. You will manage projects from requirements gathering to planning to implementation of full-stack data solutions (platform/pipelines to data tables to visualizations). You will work closely with cross-functional partners to ensure that business logic is properly represented in the semantic layer and production environments where it can be used by the wider Product Analytics team to drive business insights and strategy.

• You partner with Product stakeholders to understand business questions and build out advanced analytical solutions.

• Youll build a deep understanding of our digital streaming service and use that knowledge coupled with your engineering infrastructure data and cloud knowledge to optimize and evolve how we understand our technical ecosystem.

• To be successful youll need to be deeply technical and capable of holding your own with other strong peers.

• You have expertise practicing infrastructure-as-code data streaming pipeline data lake management Database Analytics and Dashboarding.

• You make good decisions and exercise accurate judgment when choosing to build new vs extending existing ones

• You provide guidance on design coding and operational best practices and have a track-record of applying these best practices to software that you have worked on

• You propose and proactively seek to establish best practices where none exist

• You make high impact decisions driving what and how software is built

• You design and implement data models that support flexible querying and data visualization.

• You build frameworks that multiply the productivity of the team and are intuitive for other data teams to leverage.

• You participate in the creation and support of analytics development standards and best practices.

• You create systematic solutions for solving data anomalies: identifying alerting and root cause analysis.

• You identify and explore new opportunities through creativeanalytical andengineering methods.

What to Bring:

• Bachelors Masters or higher degree in Computer Science Data Science Engineering Mathematics Statistics.

• 913 years of experience in Analytics Engineering Data Engineering Business Intelligence Data Platform Engineering or related domains.

• Proven track record of architecting scaling and operating enterprise-grade data platforms including real-time streaming pipelines data lakes data warehouses and self-service analytics ecosystems.

• Deep expertise in transforming complex incomplete and evolving data sources into trusted governed and business-ready datasets that support critical decision-making and advanced analytics.

• Extensive experience designing building and optimizing large-scale ETL/ELT pipelines workflow orchestration frameworks and data products processing millions to billions of records.

• Strong programming expertise in Python and/or Go with solid knowledge of distributed systems data structures algorithms APIs and data serialization formats.

• Strong understanding of modern application architectures including user interfaces business logic data persistence caching strategies and system integrations.

• Expertise in data modeling data architecture and performance optimization across relational (PostgreSQL preferred) and NoSQL (MongoDB preferred) platforms.

• Hands-on experience with modern data and streaming technologies including Spark Kafka Flink Databricks Snowflake and cloud-native analytics services.

• Advanced proficiency in semantic modeling business intelligence and analytics enablement using tools such as Looker Tableau or equivalent BI platforms.

• Deep knowledge of dimensional modeling data warehousing principles analytics engineering best practices and advanced SQL development across multiple database technologies.

• Strong expertise in cloud-native infrastructure containerization and Infrastructure-as-Code (IaC) using AWS/GCP Docker Kubernetes and Terraform.

• Experience implementing observability monitoring and reliability frameworks leveraging tools such as Prometheus CloudWatch Kibana OpenTelemetry and related technologies.

• Experience with enterprise analytics and data exploration platforms including Athena Redshift BigQuery Splunk and similar technologies.

• Strong understanding of machine learning fundamentals statistical modeling predictive analytics and AI-driven decision-support systems.

• Experience designing and building scalable data platforms that support the complete ML lifecycle including feature engineering experimentation model training deployment monitoring and retraining.

• Hands-on experience with modern AI/ML ecosystems and platforms such as Databricks ML Vertex AI SageMaker MLflow TensorFlow PyTorch or equivalent technologies.

• Demonstrated ability to lead technical architecture decisions establish engineering best practices and influence data strategy across multiple teams and business domains.

• Proven success partnering with Product Engineering Data Science Analytics and business stakeholders to deliver scalable data-driven solutions.

• Strong ability to navigate ambiguity solve complex business and technical challenges and drive execution with minimal direction.

• Excellent written and verbal communication skills with the ability to clearly articulate complex technical concepts to both technical and non-technical audiences.

• Experience mentoring engineers and fostering a culture of engineering excellence operational rigor and continuous improvement

Characteristics & Traits

• Naturally inquisitive critical thinker proactive problem-solver and detail-oriented.

• Positive attitude and an open mind

• Strong organizational skills with the ability to act independently andresponsibly

• Self-starter comfortable initiating projects from design to execution with minimal supervision

• Ability to manage and balance multiple (and sometimes competing) priorities in a fast-paced complex business environment and can manage time effectively to consistently meetdeadlines

• Team player and relationship builder

What We Offer:

• A Great Place to work.

• Equal opportunity employer

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 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

If youre 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.