Staff Analytics Engineer - Data Analytics Team, Hyderabad

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. 
For more information, please visit www.wbd.com
 

Meet Our Team :

The Commerce & Growth Analytics team works across acquisition and retention sciences, partnering with Product, Marketing, Engineering, Finance, and other cross-functional stakeholders to understand how customers discover, subscribe, activate, and retain Warner Bros. Discovery's streaming products. We develop and support strategic data & analytical products combining advanced analytics, statistics, experimentation, machine learning, and scalable data engineering to generate actionable insights that influence activation, monetization, and revenue growth across global markets. Working with large-scale behavioral, subscription, authentication, and payment data, we solve complex business problems and drive data-informed decision-making across the organization. 
 

About the Role :

As a Staff Analytics Engineer, you will be responsible for data pipeline, data strategy, and data visualization-related efforts for the Commerce & Growth Analytics team at WBD. You're 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 (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. 
 

Roles & Responsibilities: 

• Design and implement data models that support flexible querying and data visualization. 

• Partner with Commerce and Growth stakeholders to understand business questions and build out advanced analytical solutions. 

• Advance automation efforts that help the team spend less time manipulating and validating data and more time analyzing. 

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

• Create systematic solutions for solving data anomalies: identifying, alerting, and root cause analysis. 

• Work proactively with stakeholders to ready data solutions for new product and/or feature releases, with a keen eye for uncovering and troubleshooting any data quality issues or nuances. 

• Identify and explore new opportunities through creative analytical and engineering methods. 

• Create new or optimize existing analytics development standards and best practices. 

• Mentor and provide guidance to junior data analytics engineers on the team. 

What to Bring:

• Bachelor's degree, MS, or greater in a quantitative field of study (Computer/Data Science, Engineering, Mathematics, Statistics, etc.). 

• 9+ years of relevant experience in business intelligence / data engineering. 

• Expertise in writing SQL (clean, fast code is a must) and in data-warehousing concepts such as star schemas, slowly changing dimensions, and ELT/ETL. 

• Experience in transforming flawed/changing data into consistent, trustworthy datasets, and in developing DAGs to batch-process millions of records. 

• Experience with general-purpose programming (e.g. Python, Java, Go), dealing with a variety of data structures, algorithms, and serialization formats. 

• Experience with big-data technologies (e.g. Spark, Kafka, Hive). 

• Advanced ability to build reports and dashboards with BI tools (such as Looker and Tableau). 

• Proficiency with Git (or similar version control) and CI/CD best practices. 

• Experience managing workflows using Agile practices. 

• Expertise in writing clear, concise documentation and communicating with a high degree of precision. 

• Ability to solve ambiguous problems independently and to manage multiple projects and time constraints simultaneously. 

• Care for the quality of the input data and how the processed data is ultimately interpreted and used. 

• Strong written and verbal communication skills, and strong organizational skills with the ability to act independently and responsibly. 

• Self-starter, comfortable initiating projects from design to execution with minimal supervision, and able to balance multiple (and sometimes competing) priorities in a fast-paced, complex business environment while consistently meeting deadlines. 

• Team player and relationship builder. 

Good to Have :

• Experience with OLAP databases such as Snowflake or Redshift. 

• Experience with dbt or similar transformation and semantic-layer frameworks. 

• Experience with digital products, streaming services, or subscription products. 

• Experience with cloud data platforms such as Databricks.