Senior Lead Data Engineer, Content Engineering

🕒 May 6

🗽 New York – Remote

🗽 New York – Remote

💵 $156.8k - $235.2k / year

⏰ Full Time

🟠 Senior

🚰 Data Engineer

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Paramount

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1912

📱 Media

👥 B2C

Media • B2C • Entertainment

Paramount is a global multimedia entertainment and news company that offers a range of services including direct-to-consumer digital subscription video on-demand and live streaming through Paramount+. It also owns Pluto TV, a leading free streaming television service, MTV, the world’s premier youth entertainment brand, and CBS Sports, a leader in television sports broadcasts. Paramount Pictures, since 1912, has been a legendary producer and distributor of films, hosting a library of over 1,000 titles. The company is deeply committed to inclusion and impact, focusing on diversity, global sustainability, and content that affects change. Being a significant player in both live and on-demand streaming services, Paramount embraces a wide array of content from sports to kids’ entertainment, comedy, and groundbreaking documentaries, impacting both linear and streaming platforms globally.

📋 Description

• Build & Operate Large-Scale Feature Pipelines: Design and maintain batch/streaming pipelines (Spark, Flink, Databricks, Airflow) producing ML features for ranking models. • Ensure Point-in-Time Correctness: Develop feature sets that enable unbiased offline training and credible online inference. • Develop Embedding & Content Pipelines: Build scalable workflows for metadata, imagery, and multimodal representations; partner with Science teams to operationalize new models. • Architect Data Foundations: Design Delta/Parquet data models and medallion layers, optimizing storage layout and partitioning for latency and cost. • Real-Time Engineering: Build Kafka-based systems for real-time features and user-activity aggregations, ensuring robust handling of out-of-order events and exactly-once semantics. • Governance & Leadership: Define data quality rules and schema evolution processes while collaborating across ML pods to translate model needs into infrastructure.

🎯 Requirements

• 7+ years of experience in large-scale data or software engineering • Deep experience with Spark (PySpark/Scala), Databricks, Airflow, and Kafka. • Proficiency in feature pipelines, temporal joins, and mitigating training-serving skew. • Experience with AWS/Azure/GCP and high-performance engines like Snowflake or Redshift. • Proficient programming skills in Python and SQL with a focus on performance optimization. • Experience in personalization domains (search, ranking, or recommender systems). • Experience supporting petabyte-scale data lakehouses or feature stores. • Familiarity with GenAI/RAG systems, multimodal content, or Delta Live Tables. • Knowledge of Causal Inference, experimentation signals, or ML evaluation workflows. • Experience with Terraform for governed, repeatable deployments.

🏖️ Benefits

• medical • dental • vision • 401(k) plan • life insurance coverage • disability benefits • tuition assistance program • PTO