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Data Engineer – Self Service Analytics, Time Data Platforms

Job in Burbank, Los Angeles County, California, 91520, USA
Listing for: Jobtailor
Full Time position
Listed on 2026-07-20
Job specializations:
  • Software Development
    Data Engineering, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 120000 - 180000 USD Yearly USD 120000.00 180000.00 YEAR
Job Description & How to Apply Below
Position: Data Engineer – Self Service Analytics, Real Time Data Platforms

Responsibilities

  • Help build scalable data products, semantic layers, and real-time data platforms
  • Develop solutions that power BI, analytics, experimentation, AI applications, agents, and conversational analytics experiences
  • Design, develop, and maintain scalable batch (ETL/ELT) and near real-time streaming data pipelines
  • 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
  • Drive best practices for data quality, governance, metadata, and discoverability
Requirements
  • 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
  • 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
  • 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
  • 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
  • Excellent problem-solving skills with the ability to work in dynamic, high-velocity environments
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field (or equivalent experience)
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