Staff Analytics Engineer

As the premier global media and entertainment company, Warner Bros. Discovery offers audiences the world’s most differentiated and complete portfolio of content, brands, and franchises across television, film, sports, news, streaming, and gaming. We're home to the world’s best storytellers, creating world-class products for consumers.

WBD is bringing together the scripted and the unscripted, the local and the global, the timely and the timeless. Taking the world’s greatest possibilities and making them a reality. Creating impact, inspiring imagination, and building connections. Here you can succeed, here you are supported, here you are celebrated. From brilliant creatives to technology trailblazers and beyond, join us as we step into the next chapter.

As a Staff Analytics Engineer, you will lead data pipeline, data strategy, and data visualization-related efforts for the Global Product Analytics team at HBO 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 Global Product Analytics team to drive business insights and strategy.

Responsibilities

Design and implement data models that support flexible querying and data visualization
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
Advance automation efforts that help the team spend less time manipulating & validating data and more time analyzing it
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
Partner with GPA colleagues and Product stakeholders to understand business questions and build out data solutions
Build strong relationships with internal teams to consistently understand analytical needs and share 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 engineering methods

Qualifications

Bachelor's degree, MS or greater in a quantitative field of study (Computer/Data Science, Engineering, Mathematics, Statistics, etc.)
5+ 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, ELT/ETL, and MPP databases
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)
Experience with analytics tools such as Athena, Redshift/BigQuery, Splunk, etc.
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
Ability 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
Experience with digital products, streaming services, or subscription products is preferred
Strong written and verbal communication skills

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 and responsibly
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 meet deadlines
Team player and relationship builder

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