Data Engineer

• Develop, optimize, and maintain reliable data pipelines and processing components using Google Cloud Platform (GCS, BigQuery, Looker)
• Integrate and manage data from various sources, including marketing platforms and ad networks
• Design and maintain scalable data models and datasets that support analytics and business decision-making
• Translate business requirements into efficient, scalable data solutions
• Improve data accessibility, reliability, and performance across the data ecosystem
• Build tools and frameworks that enable faster, more effective analysis and self-service reporting
• Ensure data quality, consistency, and governance throughout the data lifecycle
• Optimize data infrastructure and processing costs while maintaining scalability and performance

• This role focuses on building the data foundations that enable advanced analytics and machine learning at scale.
• You will design and develop data pipelines and architectures that support real-time insights and AI-driven applications across the business.
• Working with large, complex datasets, you will ensure data is reliable, accessible, and optimized for both analytics and machine learning use cases.
• Develop data models and warehouse schemas optimized for analytics and machine learning.
• Build and maintain data ingestion frameworks using streaming systems (Kafka, Kinesis) and batch processing (Spark, Airflow).
• Build and manage feature stores to support ML model training and inference.
• Integrate data from multiple sources into a unified architecture.
• Implement data quality validation frameworks and monitoring systems.
• Optimize data pipelines for performance, scalability, and cost efficiency.

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