GCP Data Engineer

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.