Welcome to Warner Bros. Discovery… the stuff dreams are made of.
Who We Are…
When we say, “the stuff dreams are made of,” we’re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD’s 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 what’s 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.
Senior Software Engineer, Data Platform – Data Trust
About Warner Bros. Discovery:
Warner Bros. Discovery, a premier global media and entertainment company, offers audiences the world's most differentiated and complete portfolio of content, brands and franchises across television, film, streaming and gaming. The new company combines Warner Media’s premium entertainment, sports and news assets with Discovery's leading non-fiction and international entertainment and sports businesses.
For more information, please visit www.wbd.com
Meet Our Team:
The Data Platform Data Trust team helps to span development, execution and reporting on various data validation efforts as it relates to the Global Discovery+ & Max product includes functional and non-functional testing. The Engineer will drive the framework for technology, tools, automation initiatives for data validation across the data ecosystem. Ensuring code and pipelines are created to discover, implement, execute, and manage those tests. The Engineer will collaborate with Frontend Client and Backend service teams spread across US / EMEA / APAC teams.
Roles & Responsibilities:
Data Validation and Testing: Expertise in validating data quality, integrity, and consistency across different datasets.
SQL and Database Knowledge: Proficiency in SQL for querying and validating data in various types of databases (relational and non-relational).
Programming Languages: Knowledge of programming languages like Python or R, particularly for data manipulation, automation, and building custom validation scripts.
Engineering - Build systems and datasets to meet Data Quality objectives, using software engineering, data management, and operational best practices.
Analysis and Design - Analyze systems and data to identify data quality gap, data patterns, Detect anomalies and provide solutions. Design and document data models and transformation specifications.
Data Warehousing: Understanding of data warehousing concepts, ETL processes, and tools (e.g., Apache Airflow, Talend).
Data Quality Tools: Familiarity with tools like Apache Spark, Pandas, Great Expectations, Informatica Data Quality, Talend Data Quality, etc.
Big Data Technologies: Experience with big data frameworks like Hadoop, Apache Spark, and distributed computing environments.
API Testing: Skills in testing and validating data flows through APIs and web services.
Data Governance and Compliance: Knowledge of data governance frameworks, data privacy
Tooling Aptitude- Successful track record of instrumenting tools, automation, and processes at scale for frontend and backend Quality engineering activities (Unit, Integration, User journey, Load, payment, regression testing)
Software Quality - Understanding of automation workflows, CICD release pipelines, test environments across multiple products and release within an agile development framework.
Effectively communicate – through technical documentation, and experience using various tools and technologies such as JIRA, Confluence, GitHub.
Partner across Teams - Partner with analysts, engineers, subject matter experts, and product managers to apply WBD’s analytical and quality methods to satisfy stakeholder needs.
Improvement Driven - Experience working with DevOps teams to drive improvements in Release Tools pipeline for automated tracking and reporting on release artifacts: JIRA items, sprint scope, bug report, test report, release notes.
What to Bring:
5+ years of hands-on software and quality engineering experience focused on Data Platform & Analytics
5+ years of hands-on experience in Data Validation, building custom validation scripts and automation Data Validation pipelines
Proficiency in SQL, Data Warehousing, Data Analysis, Data Profiling and Governance concepts
Hands-on experience testing large-scale, production systems using Python, SQL, Apache Spark and Open Source Data Platform Validation Tools
Experience working with public cloud infrastructure (AWS, GCP, Azure)
AWS – 2+ years of experience with AWS Cloud Data Technologies including familiarity with EMR, Kinesis, Athena
In-depth knowledge and understanding of standard quality best practices, techniques and methodologies to drive continuous quality improvements
Ability to take a project from scoping the requirements and building the test cases
Experience with continuous integration / continuous deployment systems like Jenkins
Familiarity with Gen AI based test automation, models, processes and tools
Preferred:
Databricks – Databricks Data Engineer certification preferred. Design, develop, and deploy scalable and efficient data pipelines using Databricks,
Apache Spark, and other relevant technologies. Optimize and tune Databricks jobs and clusters for optimal performance and resource utilization.
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
Let our experts design a Professional CV for you.