Staff Analytics Engineer

at  Warner Bros Careers

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.

SKILLSET & EXPERIENCE

• Bachelor’s degree, MS or greater in a quantitative field of study (Computer/Data Science, Engineering, Mathematics, Statistics, etc.)
• 7+ years of relevant experience in advanced analytics/analytics engineering
• Expertise in writing SQL (clean, fast code is a must)
• Experience working with complex stakeholders; dissecting vague asks and outputting digestible strategic insights from data
• Advanced ability to build reports and dashboards with BI tools (such as Looker and Tableau)
• Experience in transforming flawed/changing data into consistent, trustworthy datasets, and in developing DAGs to batch-process millions of records
• Experience in data-warehousing concepts such as star schemas, slowly changing dimensions, ELT/ETL, and MPP databases
• Experience with general-purpose programming (e.g. Python, Java, Go), dealing with a variety of data structures, algorithms, & statistical analysis etc.
• Experience with big-data technologies (e.g. Spark, Kafka, Hive)
• Proficiency with Git (or similar version control) and CI/CD best practices
• Experience in managing workflows using Agile practices
• Ability to write clear, concise documentation and to communicate generally with a high degree of precision
• Ability to solve ambiguous problems independently, while prioritizing the quality of the input data and how the processed data is ultimately interpreted and used by stakeholders
• Ability to manage multiple projects and time constraints simultaneously
• Experience with digital products, streaming services, or subscription products is preferred
• Strong written and verbal communication skills, especially with senior level stakeholders

THE ROLE

As a Staff Analytics Engineer, you will lead data pipeline, data strategy, and data visualization-related efforts for the Global Product Analytics team at Max. 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, where it can be used by the wider Product Analytics team to drive business insights and strategy.

JOB RESPONSIBILITIES

• Design and implement data models that support flexible querying and data visualization.
• Partner with Product stakeholders to understand business questions and build out advanced analytical solutions.
• Advance automation efforts that help the team spend less time manipulating & validating data and more time analyzing.
• Mentor fellow engineers and help others act as successful stewards of our tools.
• Build frameworks that multiply the productivity of the team and are intuitive for other data teams to leverage.
• Guide the Analytics Engineering roadmap, communicate timelines, and manage development cycles/sprints to deliver value.
• Participate in the creation and support of analytics development standards and best practices.
• 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.