Overview
On Site
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - W2
Skills
GCP
BI
ETL
Big query
Job Details
We are seeking an experienced Google Cloud Platform Design Lead to drive the design and implementation of core data and analytics capabilities on Google Cloud Platform (Google Cloud Platform). In this role, you will play a pivotal part in enabling various business units and tenants across the organization to leverage Google Cloud Platform s data services efficiently and securely. You will lead architectural design, oversee best practices, and ensure scalable, reliable, and cost-effective solutions.
Key Responsibilities:
Lead the design and implementation of data and analytics solutions on Google Cloud Platform, including BigQuery, ETL pipelines, and BI tools.
Define and maintain technical architectures, high-level design documents, and detailed implementation diagrams.
Provide leadership and technical guidance to engineering teams and stakeholders on best practices in data management, analytics, and cloud architecture.
Collaborate closely with enterprise architects, data engineers, and business teams to align Google Cloud Platform solutions with organizational goals.
Ensure that the data and analytics services are secure, compliant, and optimized for performance and cost.
Evaluate and recommend new tools, technologies, and methodologies to continuously improve data services on Google Cloud Platform.
Required Qualifications:
15+ years of overall IT experience, with a strong focus on cloud technologies, data analytics, and solution architecture.
Proven expertise in Google Cloud Platform (Google Cloud Platform), particularly in:
BigQuery
ETL/ELT processes
BI tools (such as Looker, Tableau, Power BI)
Solid experience in designing large-scale data architectures and modern data platforms on the cloud.
Strong understanding of data governance, security, and compliance in a cloud environment.
Excellent leadership, communication, and stakeholder management skills.
Preferred Qualifications:
Google Cloud Platform certifications such as Professional Data Engineer, Professional Cloud Architect, or similar.
Experience working in multi-tenant or enterprise-wide data environments.
Knowledge of DevOps practices and CI/CD in the context of data engineering.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.