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Senior GCP Data & AI Engineer (Remote, Lahore, PKR Salary)

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Summary

Senior engineer leading data engineering and AI delivery on Google Cloud: modeling client data in BigQuery/GCS with secure RBAC, building Gemini Enterprise capabilities (RAG, AI agents, conversational analytics, MCP integrations), and shipping governed Looker/LookML analytics. Core stack: GCP, BigQuery, Gemini, Looker, SQL, Python.

Requirements:



  • 6+ years of experience leading data engineering, data architecture, and AI solution development.

  • Commercial experience with Google Cloud Platform (GCP), particularly BigQuery and Google Cloud Storage (GCS).

  • Strong understanding of data modelling, schema design, data warehousing, lakehousing, and role-based access control (RBAC).

  • Relevant GCP certification(s).

  • Hands-on commercial experience with Gemini Enterprise and Generative AI, including AI agents, conversational analytics, RAG, and grounding.

  • Knowledge of the Model Context Protocol (MCP) and experience with agent-based integrations.

  • Experience with Looker, dashboard development, semantic modelling, and LookML.

  • Strong proficiency in SQL and Python for data engineering and analytics development.

  • Proven technical leadership, independent problem-solving, and delivery management skills.

  • Excellent communication and stakeholder-management skills, with the ability to engage confidently with client heads and technical leads.


Responsibilities:



  • Connect, integrate, and model client data across multiple clouds and data sources using BigQuery and Google Cloud Storage (GCS).

  • Design scalable data models and schemas, and implement role-based access control (RBAC) to ensure secure data access.

  • Develop Gemini Enterprise capabilities, including conversational analytics, grounded search, Retrieval-Augmented Generation (RAG), and AI agents.

  • Integrate the monday.com Gemini Enterprise agent and enable data connectivity across multiple sources.

  • Develop AI-powered self-service analytics solutions for non-technical users using agent creation and the Model Context Protocol (MCP).

  • Build and maintain governed analytics solutions using Looker and LookML to ensure reliability and consistency.

  • Establish standardized, observable, and multi-tenant architectures to support reliable managed services.

  • Lead technical implementations, review solutions, guide team members, and ensure high-quality delivery.

  • Collaborate with client stakeholders and technical leaders to understand requirements and maintain strong working relationships.

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