Data Engineer Self Service Analytics and Time Data Platforms

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45939

Research

Burbank

Full-Time

On-Site

#We Are Paramount  on a mission to unleash the power of content ... you in?

We’ve got the brands, we’ve got the stars, we’ve got the power to 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.

Overview

The Data Engineering team is seeking a Data Engineer – Self-Service Analytics & Real-Time Data Platforms. In this role, you will help build scalable data products, semantic layers, and real-time data platforms. These platforms enable trusted, governed, and self-service access to data. You will develop solutions that power BI, analytics, experimentation, AI applications, agents, and conversational analytics experiences.

Key Responsibilities

Self-Service Analytics & Real-Time Data Platforms

• Design, develop, and maintain scalable batch (ETL/ELT) and near real-time streaming data pipelines. These pipelines will process large-scale structured and unstructured datasets.
• Design and maintain semantic layers, metrics frameworks, and curated data products.
• Enable self-service analytics through governed and reusable business data models.
• Implement monitoring, observability, and operational best practices.
• Develop governed data access patterns for AI, conversational analytics, and MCP-based applications.
• Build AI-ready data products that support machine learning, GenAI, AI agents, and chatbot applications.
• Partner with Product, Analytics, BI, and Engineering stakeholders to deliver trusted data solutions.
• Design scalable data models optimized for analytics, real-time reporting, and AI use cases.
• Develop reusable semantic and transformation layers that provide consistent business definitions.
• Drive best practices for data quality, governance, metadata, and discoverability.

Required Technical Skills

Advanced Data Pipeline & ETL/ELT Expertise

• 2–4+ years of experience building and scaling ETL/ELT pipelines in production environments.
• Proven experience with workflow orchestration tools such as Airflow, Composer, or similar platforms.
• Working knowledge of distributed data processing concepts.
• SQL & Data Modeling for Analytics & ML
• Expert-level SQL skills for large-scale transformation and analytics.
• Experience designing scalable warehouse schemas and ML-ready data layers.

Programming & ML Data Integration

• Proficiency in Python (or similar language) for data processing and ML pipeline integration.
• Experience with distributed processing frameworks such as Spark.
• Experience integrating data pipelines with ML platforms such as Vertex AI (preferred), Databricks ML, or equivalent. This includes model training, batch/online inference, and pipeline orchestration.
• Experience building real-time data pipelines using Kafka, Pub/Sub, or similar technologies.
• Knowledge of feature streaming, low-latency data processing, and event-driven architectures.
• Ability to work closely with the streaming team to architect and build real-time dashboards using Superset.
• Experience with lakehouse architectures and cloud data warehouses.
• Knowledge of vector databases, embeddings pipelines, and AI-serving infrastructure is a plus.

Qualifications

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field (or equivalent experience).
• 2–4+ years of experience in data engineering, data pipeline development, or related fields.
• Solid foundation in modern data engineering principles, distributed systems design, and cloud-native architectures.
• Demonstrated ability to design and operate large-scale production data systems.
• Excellent problem-solving skills with the ability to work in dynamic, high-velocity environments.
• Motivated, thorough, and committed to engineering excellence and ongoing improvement.

Paramount Streaming, a division within Paramount Global, is the home to the company's…