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Ecommerce Transformation Architect - OMS & Cloud Solutions

Job in Boca Raton, Palm Beach County, Florida, 33481, USA
Listing for: TechDigital Group
Full Time position
Listed on 2026-10-22
Job specializations:
  • IT/Tech
    Cloud Computing: Infrastructure & Operations
Salary/Wage Range or Industry Benchmark: 90000 - 150000 USD Yearly USD 90000.00 150000.00 YEAR
Job Description & How to Apply Below

Job Summary
The Big Query Administrator is responsible for the administration, monitoring, performance optimization, security, governance, and operational support of Google Cloud Big Query environments.
The role ensures the availability, scalability, reliability, and cost efficiency of enterprise data platforms while supporting analytics, reporting, AI/ML, and business-critical workloads.

Experience Level: 8 - 10 Years
Role: L2/L3 Support / Platform Administration
Support Model: 24x7 Production Support (as applicable)

Technical Skills
∙ Google Cloud Platform (GCP)
∙ Big Query Administration & Performance Tuning
∙ Big Query Reservations & Capacity Management
∙ Python Programming
∙ GCP IAM & Security
∙ Cloud Monitoring & Logging
∙ Cloud Storage
∙ Data Warehousing Concepts
∙ SQL Performance Optimization
∙ Shell Scripting
∙ Terraform
∙ Git / CI-CD Pipelines
∙ Apache Airflow / Cloud Composer (preferred)
Database Knowledge
∙ Big Query
∙ Teradata (Preferred)
∙ PostgreSQL/MSSQL/Oracle (Good to Have)
Monitoring & Operations
∙ Cloud Monitoring
∙ Ops Genie
∙ Splunk
∙ New Relic
∙ Service Now

Key Responsibilities
Platform Administration

  • Administer and maintain Google Big Query environments across Development, QA, UAT, and Production.
  • Configure and manage datasets, tables, partitions, clustering, and storage lifecycle policies.
  • Manage Big Query resource allocation, quotas, reservations, and workload management.
  • Support platform upgrades, new feature adoption, and environment provisioning.
Performance & Optimization
  • Analyze and tune Big Query SQL queries for improved performance and reduced execution cost.
  • Optimize storage structures, partitioning, clustering, and materialized views.
  • Monitor query execution patterns and recommend performance improvements.
  • Improve workload efficiency and reduce cloud spend through continuous optimization.
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