Senior Google Cloud Engineer (AI & Real-Time Analytics)

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