 Knowledge & Skills:

 Understanding and experience with Google Cloud architecture

 In-depth knowledge of database and data warehouse technologies & concepts

from Google (e.g., Big Query, Cloud SQL, Spanner, Big Table)

 Experience in enterprise scale Data modelling/Data warehouse

modernization/Cloud based data lakes 

 Build the infrastructure required for optimal extraction, transformation, and

loading of data from a wide variety of data sources using SQL and Google cloud big

data’ technologies.

 Building Data pipelines with Data proc Cluster, Data Flow, Pub sub, Cloud

Composer (Airflow), Cloud functions etc.

 Fluency in object-oriented languages, preferably Python.

 Strong understanding of distributed systems architecture.

 Data quality process experience including data cleansing, audits and alerts, triage

mechanisms & processes, and referential integrity.

 CI/CD: Release, deployment with Google Cloud build and git flow, GKE, Docker



 Requirements:

 4 years’ experience architecting with GCP Database Technologies

 2 year’s hands-on experience on GCP

 Certification like Google Cloud Professional Cloud Architect, Google Professional

Data Engineer would be a plus.

o Cloud Management Platforms,

Virtualization Strategies, Automation and Orchestration Strategies, Public

Cloud Platforms, Cloud Capacity/Performance Optimization, and Application

Migrations to a Cloud Platform with a clear understanding of how an IT

organization capitalizes upon technology to enable the business.

· Deep knowledge of cloud best practices to reduce cost of operations along

with high SLOs like five 9’s availability across tiers.

· Working knowledge and skills in cloud container services -GKE, storage

services (e.g. Cloud Storage), database services (Spanner| Big Query), digital

or infrastructure deployments that includes managing projects related to

highly virtualized solutions, digital convergence, outsourcing or systems integrations, network engineering, and security.

· Deep understanding of GCP vertex search and other AI/ML services. Must be

able to identify and solve AI/ML use cases across enterprise.

· Deep understanding of microservices patterns and hands on experience with

Microservices.

· Defining cloud adoption strategy and transformation roadmap for large scale

enterprise clients.

· Designing, architecting, implementing, and managing cloud infrastructure on

Google Cloud Platform.

Requirements:

· 5 years’ experience architecting with GCP Technologies.

· 2 year’s hands-on experience on developing enterprise cloud applications.

· Certification like Google Cloud Professional Cloud Architect would be a plus.