Google Cloud Platform Architect Data

Hartford, CT, US • Posted 1 day ago • Updated 1 day ago
Contract Corp To Corp
Contract W2
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Depends on Experience
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Job Details

Skills

  • Advanced Analytics
  • Analytics
  • Apache Hadoop
  • Apache Spark
  • Artificial Intelligence
  • Auditing
  • Clustering
  • Collaboration

Summary

We are looking for Google Cloud Platform Architect Data for our client in Hartford, CT
Job Title: Google Cloud Platform Architect Data
Job Location: Hartford, CT
Job Type: Contract
Job Description:
Pay Range: $73hr - $78hr
  • We are seeking a Google Cloud Platform Lead / Architect with strong Data Engineering expertise to design and deliver secure, scalable, and cost-optimized data platforms on Google Cloud Platform (Google Cloud Platform).
  • The ideal candidate will lead architecture design, data engineering initiatives, and DevOps automation while enabling advanced analytics and AI/ML capabilities.
Key Responsibilities:

Architecture And Solution Design:

  • Lead end-to-end architecture for data platforms on Google Cloud Platform including networking, security, compute, storage, and analytics components.
  • Define High-Level Design (HLD) and Low-Level Design (LLD) along with architecture standards and reference patterns.
  • Drive architecture decisions balancing performance, reliability, scalability, security, and cost optimization.
  • Conduct design reviews, technical audits, and architecture governance.
Data Engineering And Warehousing:
  • Design and implement scalable pipelines for structured, semi-structured, and unstructured data using batch and streaming patterns.
  • Develop and maintain ETL/ELT workflows, data models, and transformation pipelines.
  • Architect and optimize BigQuery-based data warehouse/lakehouse solutions.
  • Lead data warehouse design, including dimensional modeling, SCD strategies, conformed dimensions, and data quality rules.
  • Implement partitioning, clustering, and query performance tuning.
Google Cloud Platform Platform Engineering (Hands-On):
  • Implement and enforce security controls using IAM, service accounts, and organization policies.
  • Manage and support workloads on GKE and Compute Engine with scalability and monitoring.
  • Utilize Google Cloud Storage (GCS) for governed storage and lifecycle management.
  • Use Dataproc for Spark/Hadoop based processing.
DevOps / CI-CD / Automation:
  • Build and manage CI/CD pipelines using Git and GitHub Actions.
  • Establish DevOps best practices including Git branching strategy, environment promotion, and version management.
  • Implement automation standards and infrastructure governance.
AI/ML Enablement:
  • Collaborate with ML and Data Science teams to operationalize ML services using Vertex AI.
  • Support ML training and inference integration with data platforms.
  • Ensure compliance with AI governance, security, and audit requirements.
Required Skills / Must Have:
  • 15+ years experience as Google Cloud Platform Lead / Architect with strong data engineering background.
  • 6+ years experience with Google Cloud Platform services including:

  • IAM, VPC, GCS, BigQuery
  • Vertex AI
  • GKE
  • Compute Engine
  • Dataproc
  • GitHub Actions
  • Strong expertise in data warehouse design and distributed systems.
  • Experience creating HLD, LLD, and architecture standards.
  • Strong experience building BigQuery-based data warehouse / lakehouse solutions.
  • Experience leading data modeling and DWH design.
  • Experience with DevOps, CI/CD, and automation.
  • Experience building Google Cloud Platform-native data pipelines.
  • AI/ML enablement experience using Vertex AI.

Technical Skills:
  • Data Engineering
  • Advanced SQL
Python / PySpark:
  • Pipeline design
  • Performance tuning
  • Data quality controls
Data Warehousing:
  • Dimensional modeling
  • Distributed processing
  • BigQuery optimization
DevOps:
  • Git workflows
  • GitHub Actions
  • CI/CD pipeline automation
  • Environment management
Good to Have Skills:
  • Infrastructure as Code (Terraform / Google Cloud Platform Deployment Manager).
  • MLOps experience including model lifecycle, CI/CD for ML, experiment tracking, deployment automation, and monitoring.
  • Healthcare domain exposure.
  • Experience with Medicare STAR ratings.
Qualifications:
  • Bachelor s degree in Computer Science, Engineering, or related field.
  • Google Cloud Platform Certifications preferred:

    Professional Cloud Architect
  • Professional Data Engineer.
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.
  • Dice Id: 10516350
  • Position Id: CT_GACD_0309
  • Posted 1 day ago
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