GCP Data Architect

Tech Mahindra; Hyderabad, Pune District, Bengaluru; On-site; INR 2,800,000 - 3,800,000; Full time

Job summary

Tech Mahindra in Pan India is seeking an experienced GCP Data Architect to design and implement scalable data architectures on Google Cloud Platform, spanning BigQuery, Pub/Sub, and data pipelines with Dataflow, Dataproc, and Spark. The role emphasizes serverless deployments, IaC with Terraform, memory management, and real-time data integration.

The ideal candidate will have strong SQL, Python scripting, and governance practices to ensure secure, cost-efficient cloud solutions.

Qualifications

• Must have hands-on experience with BigQuery, Pub/Sub, and data pipelines using Dataflow/Dataproc/Spark.
• Proficiency in SQL for data querying and modeling.
• Experience with Terraform for provisioning GCP infrastructure and IaC best practices.
• GCP serverless offerings such as Cloud Functions, App Engine, and Cloud Run.
• Strong memory management and performance optimization skills.
• Design and implement messaging and event-driven architectures using Pub/Sub for real-time data processing.
• Python scripting for automation and integration with GCP APIs.

Skills

BigQuery Pub/Sub

Python

Data pipelines

SQL

Terraform

GCP serverless

Memory management

Pub/Sub messaging

Tools

Dataflow

Dataproc

Spark

Job description

GCP Data Architect

Required Technical Skill Set

Google Cloud Platform (GCP) services. Strong hands‑on experience with BigQuery Pub/Sub, data pipelines (batch and streaming) with Dataflow/Dataproc/Spark, SQL and Python

Desired Experience Range

10-15 yrs

Location of Requirement

Pan India

Desired Competencies

Must-Have

• Strong hands‑on experience with BigQuery Pub/Sub, Python, data pipelines (batch and streaming) with Dataflow/Dataproc/Spark
• Proficiency in SQL
• Serverless Computing: Leverage GCP's serverless offerings such as Cloud Functions, App Engine, and Cloud Run.
• Infrastructure as Code (IaC):Develop and manage Terraform scripts for provisioning and managing GCP infrastructure, ensuring repeatability and consistency in deployments.
• Memory Management: Optimize the performance of applications and systems through effective memory management strategies, ensuring efficient resource utilization.
• Data Integration and Messaging: Design and implement messaging and event‑driven architectures using Pub/Sub and other GCP services for real‑time data processing and integration.
• Python Scripting: Write andmaintainPython scripts for automation tasks, custom solutions, and integration with GCP APIs.
• Best Practices and Governance: Establish and enforce best practices for cloud architecture, including security, cost management, and compliance. Implement governance models to ensure consistent cloud