Google Cloud Platform Data Architect

Google Cloud Platform Data Architect

Posted Today by 1761817930

Negotiable
Outside
Remote
USA

Summary: The Google Cloud Platform Data Architect is responsible for designing and implementing data solutions using various Google Cloud services. This role involves selecting appropriate technologies, migrating existing workloads to the cloud, and ensuring data governance and security. Additionally, the architect will focus on optimizing data systems for performance and cost-effectiveness.

Key Responsibilities:

  • Architecting data pipelines that handle the ingestion, transformation, storage, and analysis of data.
  • Choosing the right mix of Google Cloud Platform services (e.g., Bigtable, AlloyDB, BigQuery, Firestore/Firebase Realtime Database, Dataflow, Pub/Sub) to meet specific business requirements.
  • Migrate existing on-prem or other-cloud NoSQL workloads to Google Cloud Platform.
  • Migrate existing on-prem or other-cloud SQL workloads to Google Cloud Platform AlloyDB.
  • Structuring data for optimal storage and query performance, which includes both relational (SQL) and non-relational (NoSQL) models.
  • Implementing security measures, data access controls, and ensuring compliance with data regulations.
  • Monitoring and tuning data systems for performance and cost-effectiveness.

Key Skills:

  • Experience with Google Cloud Platform services.
  • Strong understanding of data architecture and data modeling.
  • Proficiency in both SQL and NoSQL databases.
  • Knowledge of data governance and security practices.
  • Experience in migrating workloads to cloud environments.
  • Ability to optimize data systems for performance and cost.

Salary (Rate): undetermined

City: undetermined

Country: USA

Working Arrangements: remote

IR35 Status: outside IR35

Seniority Level: undetermined

Industry: IT

Detailed Description From Employer:
  1. Designing Data Solutions:
    • Architecting data pipelines that handle the ingestion, transformation, storage, and analysis of data.
  2. Technology Selection:
    • Choosing the right mix of Google Cloud Platform services (e.g., Bigtable, AlloyDB, BigQuery, Firestore/Firebase Realtime Database, Dataflow, Pub/Sub) to meet specific business requirements.
  3. Migration Experience
    • Migrate existing on-prem or other-cloud NoSQL workloads to Google Cloud Platform.
    • Migrate existing on-prem or other-cloud SQL workloads to Google Cloud Platform AlloyDB.
  4. Data Modeling
    • Structuring data for optimal storage and query performance, which includes both relational (SQL) and non-relational (NoSQL) models.
  5. Governance and Security
    • Implementing security measures, data access controls, and ensuring compliance with data regulations.
Optimization: Monitoring and tuning data systems for performance and cost-effectiveness