> Markdown version of [/jobs/ext/610734-data-engineer-self-service-analytics-and-real-time-data-platforms](https://www.wearedevelopers.com/jobs/ext/610734-data-engineer-self-service-analytics-and-real-time-data-platforms). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer Self Service Analytics and Real Time Data Platforms - **Company:** Paramount Pictures - **Location:** San Francisco, CA, United States - **Experience:** Experienced - **Salary:** $99,000.0 - $147,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Business Analytics Applications, Data Analysis, Computing Platforms, Cloud Computing, Cloud Database, Cloud Engineering, Computer Programming, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Security, Data Systems, Database Queries, Distributed Computing Environment, Distributed Systems, Python (Programming Language), Machine Learning, Metadata, Operational Databases, Cloud Services, Standard Sql, Azure Machine Learning, SQL Databases, Data Streaming, Data Processing, Apache Spark, Data Layers, Event Driven Architecture, Information Technology, Real Time Data, Apache Kafka, Data Management, Data Pipelines, Databricks - **Published:** June 23, 2026 - **Apply:** https://careers.paramount.com/job/Burbank-Data-Engineer-Self-Service-Analytics-and-Real-Time-Data-Platforms-CA-91505/1402140700/ ## About the Role 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. * Proven experience optimizing complex queries across multi-terabyte datasets. 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. Streaming & Event-Driven Systems * 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. Cloud & Modern AI Data Platforms * Experience designing cloud-native data architectures (GCP preferred). * Experience with lakehouse architectures and cloud data warehouses. * Knowledge of vector databases, embeddings pipelines, and AI-serving infrastructure is a plus., * 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. ## Description 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. Data Modeling & Platform Architecture * 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. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) - [Parquet, Delta, Iceberg & Ducklake - An introduction for developers](https://www.wearedevelopers.com/videos/100075-parquet-delta-iceberg-ducklake-an-introduction-for-developers) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)