Gcp Data Engineer

We are seeking a GCP Data Engineer to design and build scalable semantic data layers from unstructured and multi-modal content such as PDFs, PowerPoint presentations, and embedded images. The role focuses on developing robust data ingestion pipelines, semantic modeling, vector-based search capabilities, and enterprise data solutions on Google Cloud Platform. Exposure to Agentic AI frameworks and orchestration is desirable but secondary.

Key Responsibilities:

• Design and develop data pipelines to ingest, process, and transform unstructured data from PDFs, PPTs, and images.
• Utilize GCP services such as Document AI, Cloud Storage, BigQuery, and Vertex AI for document and image data extraction.
• Generate and manage embeddings for semantic search and retrieval using Vertex AI and BigQuery Vector Search.
• Build and maintain semantic data models that combine structured business data with unstructured content insights.
• Develop and optimize BigQuery-based data warehouses and semantic layers for analytics and reporting.
• Orchestrate end-to-end workflows using Cloud Composer (Airflow) or GCP Workflows.
• Collaborate with business and technical teams to define semantic data structures and metadata standards.
• Support integration of semantic data platforms with Agentic AI and enterprise AI applications.

Required Skills:

• Google Cloud Platform (GCP): BigQuery, Cloud Storage, Document AI, Vertex AI.
• Strong SQL and data modeling expertise.
• Experience with unstructured document processing and multi-modal data pipelines.
• Vector databases, embeddings, and semantic search implementation.
• Workflow orchestration using Airflow/Cloud Composer.
• Knowledge of Looker, dbt, or semantic layer frameworks.
• Familiarity with Agentic AI, LangChain, Genkit, or Vertex AI Agent Builder (preferred).