GCP cloud Architect

Job Description

Role: Databricks & GCP Data Platform Architect (Hands-on)

Role Purpose

We are looking for a hands-on Databricks & GCP Data Platform Architect who will design and personally implement scalable Lakehouse solutions on Google Cloud Platform (GCP).

This role requires deep technical involvement, including building pipelines, configuring Databricks, and troubleshooting production issues, in addition to architecture ownership.

Key Responsibilities

1. Architecture & Hands-on Implementation

Design end-to-end Databricks Lakehouse architecture on GCP
Hands-on implementation of:
Databricks workspaces, clusters, jobs, and workflows
Delta Lake–based Bronze / Silver / Gold data layers
Batch and streaming pipelines using Spark and Databricks
Create reference implementations and reusable frameworks for teams
Actively participate in coding, reviews, and production deployments
2. Data Engineering (Hands-on)

Build and optimize Spark jobs and Databricks notebooks
Implement ingestion pipelines from:
Databases and enterprise applications
Streaming sources (Pub/Sub, Kafka)
External and SaaS systems
Perform performance tuning and cost optimization
Troubleshoot pipeline failures and production issues directly
3. Security, Governance & Compliance

Implement (not just define) governance using Unity Catalog
Configure access control integrated with GCP IAM
Set up secure networking (VPC, private endpoints)
Enable audit logging, lineage, and data classification
Work closely with security teams to operationalize standards
4. DevOps, Automation & Operations (Hands-on)

Build CI/CD pipelines for Databricks notebooks, jobs, and configs
Implement Infrastructure as Code using Terraform
Set up monitoring, alerting, and operational dashboards
Participate in production support, root-cause analysis, and fixes
Drive hands-on cost optimization initiatives
5. Stakeholder Collaboration

Translate business requirements into implemented solutions
Guide and mentor data engineers through code-level support
Conduct architecture and code reviews
Act as a technical owner from design through production
Required Skills & Experience

Must Have

Strong hands-on experience with Databricks (Apache Spark)
Proven experience building and deploying Lakehouse architectures
Hands-on experience with GCP, including:
Google Cloud Storage (GCS)
BigQuery
Pub/Sub
IAM & VPC basics
Experience implementing batch and streaming pipelines
Strong troubleshooting and production support skills
Good to Have

Unity Catalog, Delta Live Tables
CI/CD, Git, Terraform
MLflow, Vertex AI exposure
Multi-cloud Databricks experience (Azure / AWS)
Experience & Qualifications

8–12 years of experience in data engineering / data platforms
3+ years in a hands-on architect or senior technical lead role
Job Types: Full-time, Permanent

Pay: ₹3,000,000.00 - ₹4,000,000.00 per year

Benefits:

Health insurance
Provident Fund
Application Question(s):

What's your notice period?
What's your current ctc & expected ctc?
How many years of experience you have in GCP & Databricks?
Experience:

total: * years (Preferred)
Work Location: Hybrid remote in Mumbai, Maharashtra (Mumbai)