Sr Manager Analytics Engineer

Paramount•New York, NY

11d

About The Position

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 at scale. This role has people management responsibilities.

Requirements

Bachelor’s degree in economics, Statistics, Analytics, Computer Science, MIS, Data Engineering, or related field.
7+ years of experience in analytical engineering, data engineering, or data analytics with solid SQL and data modeling expertise.
Deep knowledge of ETL/ELT principles, data architecture, and performance optimization.
Proven experience building scalable data products and pipelines using tools such as Databricks, Airflow, Spark, or similar platforms.
Direct experience with modeling and maintaining content metadata pipelines, including working with title catalogs, rights and windowing data, genre and talent taxonomies, or similar structured data in entertainment or media.
Proficient ability to collaborate with both technical and non-technical stakeholders to deliver high-impact data solutions.
Fluency in building and maintaining production-grade datasets in cloud-based data environments (e.g., Snowflake, Redshift, BigQuery).
Proficiency with BI tools such as Looker and Tableau, including building curated data layers and performance tuning.
Solid data hygiene practices, including version control, code reviews, unit testing, and documentation.
Exemplary problem-solving skills and attention to detail, especially when reconciling metadata inconsistencies across systems.

Nice To Haves

Experience working with content rights and licensing data, including availability windows, territory restrictions, and content lifecycle management.
Knowledge with content taxonomy and classification systems used in entertainment or media.
Proficiency in Python or another scripting language for data transformation or orchestration.
Knowledge with streaming media or direct-to-consumer digital products.
Experience implementing anomaly detection systems or contributing to root cause investigations for metadata issues.
Knowledge of data governance and compliance best practices as they relate to licensed content.

Responsibilities

Design, build, and maintain scalable data pipelines that manage content metadata like titles, rights and licensing windows, genres, talent, franchise or series hierarchies, and availability.
Develop and improve reliable data models that unify content metadata from different sources, including ingest, catalog management, licensing, and rights management systems, to support detailed reporting at the title, franchise, and window levels.
Collaborate with software and data engineering teams to ensure metadata is complete, precise, and consistent, identifying issues such as duplicate titles, missing or conflicting rights windows, incorrect genre or talent tagging, and misclassified territories.
Contribute to anomaly detection systems and operational dashboards that track content catalog health, metadata completeness, and data quality KPIs.
Translate business needs into technical data solutions by working closely with analysts, content operations, programming teams, licensing, and product managers.
Build scalable, performant datasets in platforms such as Databricks, Looker, and Snowflake to enable self-service analytics for content stakeholders.
Lead the creation and maintenance of clear technical documents and set coding standards and practices for data governance, focusing on metadata taxonomy standards and ensuring compliance with content rights.