Technical Lead (Data & AI) - GCP

Quadrant Technologies India Pvt Ltd; India; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Quadrant Technologies India Pvt Ltd is seeking a Senior Data Engineer with deep experience in Google Cloud, BigQuery, and Gemini Enterprise. You will shape presales solutions, design data platforms, and drive AI-enabled data projects for global customers.

The role requires strong SQL/Python, data modeling, and hands-on cloud experience across data services, with a focus on adoptions of GenAI and agentic AI within enterprise data environments.

Qualifications

• Bachelor’s degree in CS/Engineering/IT or related field.
• Google Cloud certifications preferred.
• 8–10 years of IT experience.

Responsibilities

• Partner with Sales and the Data Practice Head to qualify opportunities, conduct discovery, and shape Google BigQuery and Gemini Enterprise-led solutions.
• Lead technical solution design, estimates, assumptions, risks, dependencies, and implementation approaches for presales opportunities.
• Support RFIs/RFPs, customer workshops, architecture presentations, demonstrations, and proofs of concept.
• Articulate Google BigQuery and Google Cloud differentiators across scalability, security, governance, performance, analytics, AI integration, and cost.
• Identify, prioritize, and demonstrate agentic AI use cases using Gemini Enterprise and the Gemini Enterprise Agent Platform, and build agent proofs of concept connected to BigQuery and enterprise data sources.
• Collaborate with architects and delivery teams to validate feasibility and ensure a complete handoff from sales to execution.
• Develop reusable accelerators, reference designs, AI agent templates, case studies, proposal assets, and practice collateral.
• Mentor team members and support interviews, certifications, and Google Cloud data and AI capability development.
• Maintain opportunity status, presales metrics, and pipeline updates for the Data Practice Head.

Skills

BigQuery

SQL

Python

Data engineering

GCP data services

Gemini Enterprise

Agent Platform

RAG/GenAI use cases

Education

Bachelor’s degree in Computer Science/Engineering/IT

Google Cloud certifications (e.g., Professional Data Engineer, Professional Cloud Architect, Generative AI Leader, Professional Machine Learning Engineer)

Tools

Looker

Vertex AI

Terraform

Cloud Dataflow

Job description

Quadrant Technologies India Pvt Ltd | Full time

• 1)8 to 10 years of total experience in Information Technology.
• 2) 4+ years of hands-on experience in data engineering, analytics, or clouddata platforms, including 2+ years on Google Cloud and BigQuery.
• 3) 1+ years of hands-on experience with Generative AI or agentic AIsolutions on Google Cloud, preferably Gemini Enterprise and Gemini EnterpriseAgent Platform (formerly Vertex AI).
• 4) 2+ years of experience supporting presales, solution consulting,technical sales, or practice development.
• 5) Experience working with global customers and onsite/offshore deliverymodels.

AcademicQualification

Bachelor’sdegree in Computer Science, Engineering, Information Technology, or a relatedfield. Google Cloud certifications (e.g., Professional Data Engineer,Professional Cloud Architect, Generative AI Leader, Professional MachineLearning Engineer) are preferred.

PrimarySkills

• 1)Strong hands-on knowledge of Google BigQuery, including data modeling,partitioning, clustering, materialized views, performance tuning, workloadmanagement, and cost optimization.
• 2) Experience with Google Cloud data services such as Cloud Storage,Dataflow, Dataproc, Pub/Sub, Cloud Composer, Dataplex, Data Catalog, andLooker.
• 3) Hands-on proficiency in SQL, Python, Apache Beam or Spark, datapipelines, security, governance, and IAM.
• 4) Experience designing data engineering, data warehousing, BI/analytics,AI/ML, and cloud migration or modernization solutions on Google Cloud.
• 5) Hands-on experience with Google Gemini Enterprise and the GeminiEnterprise Agent Platform, including Agent Studio, Agent Development Kit(ADK), Agent Garden (prebuilt agent samples), Agent Runtime, RAG Engine,Vector Search, the no-code Workflow Builder, and Google-made agents such asData Insights for BigQuery and Deep Research.
• 6) Ability to design agentic AI and GenAI use cases grounded on enterprisedata in BigQuery, including retrieval-augmented generation (RAG), BigQueryML, Gemini in BigQuery, and data/conversational analytics agents.
• 7) Ability to translate business requirements into solution designs,technical approaches, effort estimates, implementation plans, demonstrations,proofs of concept, and RFI/RFP responses.

SecondarySkills

• 1)Working knowledge of CI/CD, GitHub or Cloud Build, Terraform, infrastructureas code, and DataOps/MLOps practices.
• 2) Understanding of BigQuery pricing, slot reservations, capacity planning,workload sizing, FinOps, and cloud consumption optimization.
• 3) Understanding of Gemini Enterprise editions (Standard/Plus) andlicensing, Agent Gallery and Agent Marketplace, agent governance (AgentGateway, Identity & IAM, Model Armor), Responsible AI, and agentinteroperability standards such as Agent2Agent (A2A) and Model ContextProtocol (MCP).
• 4) Familiarity with Looker, Vertex AI, partner ecosystems, competitivepositioning (e.g., Microsoft Copilot Studio, AWS Bedrock Agents, DatabricksMosaic AI), proposal development, SOW creation, and sales qualificationprocesses.

Responsibilities

• 1)Partner with Sales and the Data Practice Head to qualify opportunities,conduct discovery, and shape Google BigQuery and Gemini Enterprise-ledsolutions.
• 2) Lead technical solution design, estimates, assumptions, risks,dependencies, and implementation approaches for presales opportunities.
• 3) Support RFIs/RFPs, customer workshops, architecture presentations,demonstrations, and proofs of concept.
• 4) Articulate Google BigQuery and Google Cloud differentiators acrossscalability, security, governance, performance, analytics, AI integration,and cost.
• 5) Identify, prioritize, and demonstrate agentic AI use cases using GeminiEnterprise and the Gemini Enterprise Agent Platform, and build agent proofsof concept connected to BigQuery and enterprise data sources.
• 6) Collaborate with architects and delivery teams to validate feasibilityand ensure a complete handoff from sales to execution.
• 7) Develop reusable accelerators, reference designs, AI agent templates,case studies, proposal assets, and practice collateral.
• 8) Mentor team members and support interviews, certifications, and GoogleCloud data and AI capability development.
• 9) Maintain opportunity status, presales metrics, and pipeline updates forthe Data Practice Head.

Soft Skills

• 1)Executive-level communication, storytelling, presentation, and consultativeselling skills.
• 2) Ability to influence business and technical stakeholders and simplifycomplex concepts.
• 3) Strong ownership, collaboration, negotiation, time management, andcustomer-facing skills.