Role- GCP Data Architect

Experience-12–18 years overall experience; 4–8+ years GCP; multiple platform implementations

Location- PAN INDIA

Required Skills & Expertise

- GCP Services: BigQuery, GCS, Pub/Sub, Dataflow, Dataproc, Dataplex, Dataform, Composer
- Programming: Python, PySpark, Beam, SQL
- Streaming: Kafka, Pub/Sub
- IaC & DataOps: Terraform, Source Repository, Github, Cloud Build, Jenkins, Artifact Registry
- Data Governance: IAM, DLP, tagging, lineage tools
- Data Migration: Data Migration Services, Dataproc, Dataflow, Data Fusion, Data Stream, Storage Transfer

Role Summary Seasoned GCP Data Architect with expertise in design, implement, and operationalizing enterprise-grade data analytics platforms on Google Cloud. Robust experience in platform engineering, data migration strategies, data ingestion patterns, governance, observability, DataOps, and scalable data architecture.

Core Responsibilities

- GCP Data Analytics Platform (Greenfield & Modernization)

Design and deploy enterprise data platform architecture; environment setup; architecture pattern - data Lakehouse / data mesh architecture; data observability, Infrastructure Provisioning, VPC Setup. IAM Policies / Service Accounts, Data Protection at Rest and Transit, Guardrails.
- Data Migration Strategy

Design and implement end-to-end data migration strategies from on-prem/legacy systems (Historical and Incremental) to GCP. (Data Migration Service, BigQuery Migration Service)




- Data Ingestion Patterns

Design and implement scalable ingestion frameworks supporting multiple pattens - Batch / Realtime / API-Based Ingestions (GSUtil, Kafka, Pub Sub, Data Stream)
- Data Engineering Pipelines (Batch and Streaming)

Build and optimize the end-to-end data engineering batch and Realtime / near Realtime steaming pipelines to build data products / data marts (BigQuery, Dataflow, Dataproc, Dataform, DBT, GCS, Composer)
- Data Governance & Security

Implement enterprise grade data governance and compliances – data security RBAC controls, data classification and tagging, data discovery, data lineage, metadata management. (Dataplex, IAM, DLP, Data Catalog)
- Data Observability Framework

Implement centralized monitoring frameworks - data engineering pipeline monitoring, data lineage tracking and alerting mechanism (Cloud Logging and Monitoring)
- DataOps & Platform Automation

Implement data operation / orchestration pipeline to automate build, test and deployments with infrastructure provisioning automation (Source Repository, Cloud Build, Artifact Registry, Composer, Terraform)
- Performance & Cost Optimization

Optimize platform performance and cost – BigQuery Optimization – Partitioning and Clustering, Query Optimization, Storage Life Cycle policies, FinOps (BigQuery, Denormalization, Star and Snowflake Schema, Query Tuning, FinOps)

📌 GCP Data Architect (Chennai)
🏢 Tata Consultancy Services
📍 Chennai