Role- Google Cloud Platform Cloud Data Architect ( Google Cloud BigQuery )
Location: ( Wilmington DE {OR} New Jersey ) Onsite Role
Exp Req : 12+
The Google Cloud Platform Cloud Data Architect will serve as the key technical leader responsible for the comprehensive end-to-end data architecture, design, and governance of the Google Cloud BigQuery platform, ensuring scalable, secure, and cost-effective analytics solutions.
Mandate Skills:
----*****Sqoop, DataFlow, DataProc, Cloud Pub/Sub, Cloud Composer, PySpark, Python, GCS, BigQuery, DAG, DataPlex *****
Certifications: (Good to have)
- Google Cloud Platform Cloud Architect
- Google Cloud Platform Professional Data Engineer
- Exp: 12-16 Yrs
Job Description:
Data Architect - Architectural Strategy: Design and implement a scalable, cost-optimized BigQuery architecture leveraging advanced features such as partitioning, clustering, and materialized views to maximize performance and minimize costs
- Data Modeling: Develop robust enterprise data models and semantic layers to support comprehensive analytics, reporting, business intelligence, marketing campaign optimization, and advanced data science use cases
- Business Engagement: Act as a trusted advisor to executives and business teams, translating business objectives into technical solutions that drive measurable outcomes
- Data Management: Define and implement master and reference data strategies to ensure data consistency, accuracy, and governance across multiple domains
- Data Quality Automation: Lead initiatives to automate data quality assurance by creating business transformation rules, automated checks, and reconciliation frameworks to uphold high data integrity standards
- Testing & Validation: Collaborate with QA teams to review and validate test cases, ensuring full coverage of business use cases and requirements, and rigorously assess data quality results
- Integration & Deployment: Coordinate across multiple teams to manage system dependencies, validate integration points, and support seamless system deployment activities
- User Acceptance Testing (UAT) & Production Rollouts: Work closely with business and IT stakeholders to coordinate UAT signoffs and oversee production cutovers, ensuring smooth deployment with well-defined fallback and contingency plans
- Governance & Security: Establish and enforce data governance standards including IAM role configurations, encryption policies, metadata management, and data lineage tracking
- Cost & Performance Optimization: Continuously monitor BigQuery usage and performance metrics to recommend and implement strategies for query optimization, and storage lifecycle policies to balance performance with cost efficiency
Stephen
Lead Talent Acquisition Specialist
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