Sr Manager Analytics Engineer

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We’ve got the brands, we’ve got the stars, we’ve got thepowerto achieve our mission to entertain the planet – now all we’re missing is… YOU! Becoming a part of Paramount means joining a team of passionate people who not only recognize the power of content but also enjoy a touch of fun and uniqueness. Together, we co-create moments that matter – both for our audiences and our employees – and aim to leave a positive mark on culture.

Paramount Streaming is a division of Paramount that encompasses both free, paid, and premium streaming services including Paramount+ and Pluto TV.

We are the Global Content and Lifecycle Analytics team, part of the Paramount Streaming, Data & Insights Group (DIG) team.

DIG is a key connector among the Paramount Streaming verticals. The group includes experts who create and improve data systems and products. They evaluate, combine, and analyze data. They develop insights and stories from both qualitative and quantitative data. Their work helps stakeholders make decisions. It also helps them understand performance and receive business recommendations.

In this important role, you will develop and maintain scalable data pipelines. You will build reliable core business reasoning. You will ensure high data quality standards for content metadata. This includes titles, rights, taxonomy, and catalog data that support Paramount's streaming business.

You will work closely with analysts, data engineers, content operations, programming, licensing, and product teams. Your goal is to convert basic metadata feeds and content data into reliable datasets, dashboards, and insights. These will support decision-making for Paramount+, Pluto TV, and other Paramount streaming services.

This role is ideal for someone who thrives at the intersection of engineering and analytics and wants to drive data excellence s role has people management responsibilities.

Pipeline Ownership:
Design, build, and maintain scalable data pipelines. These pipelines will manage content metadata like titles, rights and licensing windows, genres, talent, franchise or series hierarchies, and availability. You will work with data engineering and analytics teams. Content Metadata Modeling:
Develop and improve reliable data models. These models will unify content metadata from different sources. This includes ingest, catalog management, licensing, and rights management systems. They will support detailed reporting. This reporting will be at the title, franchise, and window levels.

Data Quality:
Collaborate with software and data engineering teams. Make sure the metadata is complete, precise, and consistent. This involves identifying issues such as duplicate titles, missing or conflicting rights windows, incorrect genre or talent tagging, and misclassified territories.

Performance Monitoring:
Contribute to anomaly detection systems and operational dashboards that track content catalog health, metadata completeness, and data quality KPIs. Collaboration across functions is important. You will work closely with analysts. Collaborate with content operations, programming teams, licensing, and product managers. You will translate business needs into technical data solutions.

Tooling & Enablement:
Build scalable, performant datasets in platforms such as Databricks, Looker, and Snowflake to enable self-service analytics for content stakeholders.

Documentation & Standards:
Lead the creation and maintenance of clear technical documents. Set coding standards and practices for data governance. Focus on metadata taxonomy…