Senior Google Cloud Engineer (AI & Real-Time Analytics)
Location: New York City, NY (Hybrid/On-site)
Type: Contract
Experience Level: Senior (7+ Years Total, 5+ Years Google Cloud Platform)
Sesheng LLC is seeking a highly skilled Senior Google Cloud Engineer for a strategic contract engagement in New York City. This role is pivotal for an initiative centered on integrating advanced AI capabilities with high-velocity streaming data. You will be responsible for designing and implementing robust architectures on Google Cloud Platform (Google Cloud Platform) that support real-time feed analytics and sophisticated AI-driven insights.
#Google Cloud Platform #GoogleCloudPlatform #AI #Dataflow #StreamingAnalytics #CloudEngineering
Key Responsibilities
· Architect & Deploy: Lead the design and deployment of scalable, secure, and highly available infrastructure on Google Cloud Platform.
· AI Integration: Implement and optimize AI/ML workflows using Vertex AI, ensuring seamless integration with existing data pipelines.
· Streaming Analytics: Develop and maintain real-time data processing pipelines using Google Cloud Dataflow, Pub/Sub, and BigQuery.
· Real-Time Feed Management: Architect solutions for low-latency ingestion and analysis of live data feeds to drive immediate business intelligence.
· Optimization: Perform deep-dive performance tuning and cost optimization for cloud-native AI and analytics services.
· Collaboration: Work closely with data scientists and stakeholders to translate complex business requirements into technical cloud solutions.
Required Qualifications
· Overall Experience: Minimum of 7+ years in DevOps, Data Engineering, or Cloud Architecture.
· Google Cloud Platform Expertise: At least 5 years of hands-on experience specifically within the Google Cloud ecosystem.
· Streaming & Real-Time Analytics: Proven track record with streaming technologies (Apache Beam, Flink, or Dataflow) and managing real-time data feeds.
· AI/ML Foundations: Practical experience deploying and scaling AI models within a cloud environment.
· Technical Stack: Proficiency in Python, SQL, and Terraform (or equivalent IaC tools).
· Education: Bachelor’s degree in Computer Science, Engineering, or a related technical field.
Preferred Qualifications
· Google Cloud Platform Certification: Professional Google Cloud Architect, Professional Data Engineer, or Professional Machine Learning Engineer certification is highly preferred.
· Experience in the financial services or healthcare sectors dealing with high-frequency data.
· Familiarity with containerization (GKE, Docker) and microservices architecture.
#Google Cloud Platform #GoogleCloudPlatform #AI #Dataflow #StreamingAnalytics #CloudEngineering
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