Data Architect

Prodapt - Irving, TX

Full-time

Irving, TX

About the position

The GCP Data Architect will be responsible for designing, creating, and managing the data architecture of the organization. This role is crucial for implementing robust, scalable, and secure data solutions on the Google Cloud Platform (GCP), ensuring that the data models align with organizational goals and stakeholder requirements. The architect will work closely with various teams to develop high-performance cloud solutions that are reliable and efficient.

Responsibilities

• Design and optimize database models to store and retrieve company information.
• Migrate data from legacy systems to new solutions.
• Create conceptual and logical data models and flowcharts.
• Develop and implement Google Cloud Platform (GCP) based solutions tailored to business needs.
• Work closely with development and operations teams to ensure seamless integration and deployment.
• Establish and maintain cloud architecture standards and best practices.
• Monitor and optimize cloud infrastructure for performance and cost-efficiency.
• Ensure the security and compliance of cloud solutions, adhering to industry standards and regulations.

Requirements

• Proficiency in SQL, Oracle, and other database management systems.
• Deep understanding of GCP services like BigQuery, Cloud Storage, Cloud SQL, DataProc, Cloud Composer and Dataflow.
• Proficiency in languages such as Python, Java, R and SQL.
• Experience with Kubernetes, Docker and containers, particularly on GCP.
• Knowledge of automation technologies like Terraform, Google Cloud Deployment Manager.
• Strong understanding of cloud architecture design, evaluation, and research.
• Perform thorough technical discovery, identifying problem areas, technical and business requirements.
• Evaluate potential solutions using both technical and commercial criteria.
• Manage clients and/or projects, ensuring successful delivery of solutions.
• Strong problem-solving abilities to address data-related issues.
• Capability to analyze and interpret complex data sets.
• Precision in designing and implementing data models.