Senior Data Architect (India)

Senior Data Architect (India)

11 Nov
|
egrove systems pvt.ltd
|
India

11 Nov

egrove systems pvt.ltd

India

Job Description – Senior Data Architect

Experience: 9–14 Years
Location: Remote
Employment Type: Contract
Budget: Up to ₹1.3 LPM
Background Verification: Basic BGV

Job Overview

We are looking for an experienced Senior Data Architect to lead the design and implementation of enterprise-scale data architecture on Google Cloud Platform (GCP). The ideal candidate should have strong expertise in GCP data services, data lakehouse architecture, data governance, graph-based data modeling, AI retrieval, embeddings and Generative AI platforms.

The candidate will drive end-to-end data architecture decisions, build scalable and secure data ecosystems, and enable AI-ready enterprise data platforms.

Key Responsibilities

- Design and implement end-to-end enterprise data architecture using Google Cloud Platform.
- Lead data lakehouse architecture using BigQuery, BigLake, Apache Iceberg and Cloud Storage.
- Architect scalable data ingestion, processing and transformation pipelines.
- Implement enterprise data governance, metadata management, data lineage and data quality frameworks.
- Design graph-based data models, knowledge graphs, ontologies and semantic layers.
- Build AI-ready data platforms supporting RAG, GraphRAG, vector search and embedding-based retrieval.
- Leverage Vertex AI, Gemini and other Google AI services for enterprise GenAI and agentic AI solutions.
- Define cloud security, networking, IAM and data protection strategies.
- Lead architecture reviews, technical decision-making and cloud modernization initiatives.




- Collaborate with cross-functional engineering teams and business stakeholders.

Required Technical Skills

1. GCP Data Platform

- BigQuery, BigLake, Cloud Storage, Cloud Spanner and BigQuery Graph.

2. Data Engineering

- Dataflow, Apache Beam, Pub/Sub, Dataproc, Cloud Composer and Dataform.

3. Data Lakehouse

- Apache Iceberg, Parquet, open table formats and cross-cloud data integration.

4. Data Governance

- Dataplex, Knowledge Catalog, metadata management, data lineage and data quality.

5. Graph & Semantic Modeling

- Cloud Spanner Graph, GQL, graph modeling, ontologies and semantic layers.

6. AI & Generative AI

- Vertex AI, Gemini, Model Garden, Vertex AI Search, Agent Runtime, ADK, A2A and MCP.

7. AI Retrieval & Embeddings

- RAG, GraphRAG, Vertex AI Embeddings, BigQuery Vector Search, Vertex AI Vector Search, hybrid search, re-ranking and Document AI.

8. AI Governance & Evaluation

- Responsible AI, Model Armor, Sensitive Data Protection (DLP), GenAI evaluation, LLMOps and AgentOps.

9. Cloud Security & Networking

- VPC, Shared VPC, VPC Service Controls, Private Service Connect, IAM, Cloud KMS and Secret Manager.

10. DevOps & Architecture

- Terraform, Cloud Build, Artifact Registry, Cloud Logging, Cloud Monitoring,



enterprise data modeling and distributed data architecture.

Required Qualifications

- 9–14 years of experience in data architecture, enterprise data platforms or solution architecture.
- Minimum 3+ years of hands-on Google Cloud Platform architecture experience.
- Proven experience designing and implementing enterprise-scale data platforms.
- Strong knowledge of data lakehouse architecture and cloud modernization.
- Experience in enterprise data governance, graph modeling and semantic architecture.
- Strong understanding of AI-ready data platforms, RAG and vector search architectures.
- Experience leading technical teams and architecture-level discussions.
- Google Professional Data Engineer or Professional Cloud Architect certification is preferred.

Good to Have

- Experience with enterprise knowledge graphs, ontology and Neo4j.
- Exposure to MCP, ADK, LangGraph and LangChain.
- Experience with Legal, Risk and Compliance data platforms.
- Hands-on experience taking GenAI and agentic AI solutions from PoC to production.
- Knowledge of model fine-tuning, context caching and Responsible AI frameworks.
- Experience with AI evaluation, observability, cost optimization and latency tuning.

Candidate Profile

The ideal candidate should be a hands-on technical architect with solid GCP expertise, capable of designing secure, scalable and AI-enabled enterprise data ecosystems while leading architecture decisions and engineering teams.

Pay: ₹130,000.00 - ₹140,000.00 per month

Work Location: Remote

📌 Senior Data Architect (India)
🏢 egrove systems pvt.ltd
📍 India

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