We are looking for a hands-on Data Engineer to build and maintain robust, scalable data solutions. Your primary focus will be developing complex data pipelines within the GCP ecosystem, ensuring high performance in both real-time and batch processing. You will work closely with architects to translate modern data strategies (like Data Mesh or Data Vault) into functional technical reality.

Core Responsibilities

Data Pipeline Development: Build, deploy, and optimize end-to-end ETL/ELT processes using GCP-native technologies (BigQuery, Dataflow, etc.).
Advanced Data Modeling: Implement sophisticated relational and Big Data structures tailored for high-volume environments.
Modern Architecture Implementation: Practically apply frameworks such as Data Fabric, Data Mesh, and Data Vault within the data platform.
Real-time Processing: Develop and maintain systems for stream processing and data warehousing aggregations to support instant analytics.
Technical Collaboration: Actively participate in design workshops, providing technical insights and ensuring the feasibility of architectural choices.

Technical Requirements

Professional Experience: 5+ years of hands-on experience in engineering complex, enterprise-grade data solutions.
GCP Expertise: Minimum 3 years of practical experience specifically within the Google Cloud Platform.
Tech Stack: Strong command of BI, ETL, and Big Data technologies (e.g., Spark, Airflow, dbt).
Data Design: Deep understanding of modern data warehousing, including real-time data flow and complex aggregations.

GCP Data Engineer

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