Google Cloud Platform Data Platform Architect

$131,100 - $302,400/Yr

Accenture - New York, NY

Full-time - Senior

New York, NY

10,001+ employees

Professional, Scientific, and Technical Services

About the position

The Google Cloud Platform Senior Data Platform Architect at Accenture is responsible for designing, implementing, and managing scalable and secure data solutions on the Google Cloud Platform. This role involves leading technology innovation for clients, collaborating with various teams to understand data requirements, and translating them into robust architectural blueprints. The position requires a deep understanding of Google Cloud Platform's data services, data warehousing, big data technologies, and data security best practices, making it essential for candidates to possess a broad set of technology skills across these areas.

Responsibilities

• Design and implement end-to-end data solutions on Google Cloud Platform, encompassing data ingestion, storage, processing, transformation, and analytics.
• Architect, design, and deploy data warehouses and data lakes, utilizing technologies like BigQuery, Dataflow, and Dataproc.
• Design and implement big data solutions on Google Cloud Platform, including data pipelines, streaming analytics, and machine learning workflows.
• Establish and maintain robust data security frameworks, implement access controls, and ensure data governance practices.
• Monitor, analyze, and optimize data platform performance to ensure optimal efficiency and cost-effectiveness.
• Stay updated on the latest Google Cloud Platform data technologies, evaluating and recommending their adoption within the organization.
• Work collaboratively with data engineers, data scientists, business analysts, and other stakeholders to understand requirements and deliver optimal solutions.
• Develop clear and comprehensive documentation, including architectural diagrams, design specifications, and operational guidelines.

Requirements

• Minimum of 3+ years of professional experience with Google Cloud Platform data services, including BigQuery, Dataflow, Dataproc, Cloud Storage, Pub/Sub, and related technologies.
• Minimum of 6+ years of strong proficiency in data warehousing concepts, data modeling, and ETL/ELT processes.
• Minimum of 6+ years of professional experience with big data technologies such as Hadoop, Spark, and NoSQL databases.
• Deep understanding of data security principles and best practices on Google Cloud Platform with minimum 3+ years of professional experience.
• Minimum of 6+ years of technical solutions implementation, architecture design, evaluation, and investigation in a cloud environment.

Nice-to-haves

• Experience working in Google Cloud Platform cloud - Organization policies, IAM, VM, DB, Kubernetes & Containers.
• Proficiency in using Google Cloud's Vertex AI platform for building, deploying, and managing machine learning models, including GenAI models.
• Experience with Generative AI Studio for prototyping and experimenting with generative AI models.
• Familiarity with Google's Model Garden and its offerings for accessing and deploying pre-trained GenAI models.
• Experience in implementing MLOps practices for the development, deployment, and monitoring of GenAI models.

Benefits

• Competitive salary based on location and experience.
• Opportunities for professional development and certifications.
• Inclusive culture that values diversity and collaboration.