Gcp Data Engineer

LatentView; Chennai District; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

LatentView is seeking a GCP Data Engineer in Chennai to design scalable semantic data layers from unstructured content such as PDFs, PPTs, and images. You will build ingestion pipelines, semantic models, embeddings, and vector search with Vertex AI and BigQuery.

You will collaborate with business and tech teams to define data structures and metadata, orchestrate end-to-end workflows with Cloud Composer or Workflows, and enable enterprise AI applications across the platform.

Qualifications

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

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.

Skills

SQL

Data modeling

Unstructured data processing

Semantic search

Vector embeddings

GCP

Airflow / Cloud Composer

Looker / dbt

Agentic AI / Vertex AI Agent Builder

Tools

BigQuery

Cloud Storage

Document AI

Vertex AI

Airflow

Cloud Composer

LangChain

Genkit

Vertex AI Agent Builder

Looker

dbt

Job description

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).