Job description

How You Will Make an Impact/ Job Responsibilities:

Design, implement, and maintain highly available, scalable, and reliable infrastructure
Working closely with client and delivering outcomes per the SoW and SLA
Architect, design, develop, deploy and document new systems or maintain existing systems on Cloud Platforms based on specifications.
Collaborate with, provide continuous guidance to, and influence design decisions of various Agile development teams for various existing and new products and solutions w.r.t. Cloud enablement, migration and infrastructure needs, to adopt and promote Cloud best practices, and economies of scale.
Engage customers understand their use cases and operational needs, as well as engage with Cloud Platform vendors to understand their technology roadmaps and evolution and translate to comprehensive technology guidance for various product teams.
Design for Cloud security and compliance ensure solutions and operations reliability.
Drive and conduct audits on current cloud utilization and recommend cloud optimization and security changes.
Act as a mentor and technical consultant for the various teams.

Desired/Preferred Skills:

Responsibilities:

Platform Management : Oversee the architecture and management of GCP resources, particularly BigQuery, Databricks, and Kubernetes.
Architecting Solutions : Design scalable and efficient data architectures tailored to specific business needs.
Optimization of Workloads : Analyze and optimize data processing workloads to improve performance and reduce costs.
Performance Measurement : Implement monitoring and performance metrics for data pipelines and applications.
Cost Monitoring : Develop strategies for cost-effective resource usage, including budget tracking and optimization techniques.
Collaboration : Work closely with data engineers, developers, and stakeholders to ensure seamless integration and functionality.

Required Skills:

GCP Expertise : In-depth knowledge of Google Cloud Platform services, particularly BigQuery, Databricks, and Kubernetes.
Data Engineering : Experience with data modeling, ETL processes, and data warehousing.
Performance Tuning : Proven track record in optimizing data processing and query performance in BigQuery.
Kubernetes Management : Proficient in deploying and managing containerized applications using Kubernetes.
Cost Management : Familiarity with GCP billing and cost management tools to monitor and optimize cloud expenditure.
Monitoring Tools : Experience with GCP monitoring and logging tools (e.g., Stackdriver, Cloud Monitoring).

Google Cloud Platform Architect