We are seeking a seasoned Data Architect with extensive experience in Google Cloud Platform (GCP) to join our dynamic team. The ideal candidate will be responsible for designing and managing robust data infrastructures leveraging GCP technologies. This role requires a deep understanding of data architecture, integration, and performance optimization.
Experience. 15+ years
Key Responsibilities
- Data Infrastructure Design. Develop and implement scalable data architectures using GCP services, including BigQuery, Cloud Storage, and Cloud SQL, ensuring high availability and reliability.
- Data Integration. Design and manage ETL processes to seamlessly integrate data from various sources into the GCP environment, enhancing data accessibility and usability.
- Performance Optimization. Continuously optimize data storage and retrieval processes to guarantee high performance and reliability of data operations.
- Security and Compliance. Implement robust data security measures and ensure compliance with relevant regulations and industry standards to protect sensitive information.
- Collaboration. Collaborate closely with data engineers, data scientists, and other stakeholders to understand data requirements and deliver tailored solutions that meet organizational needs.
- Monitoring and Maintenance. Monitor data systems for performance issues, proactively identifying and implementing necessary improvements to enhance system functionality.
- Documentation. Create and maintain comprehensive documentation for data architectures, processes, and best practices to facilitate knowledge sharing and onboarding.
Key Skills
- GCP Expertise. Proficiency in GCP services such as BigQuery, Cloud Dataflow, Cloud Pub/Sub, and Cloud Storage is essential.
- Data Modeling. Strong skills in designing conceptual, logical, and physical data models to support various business needs.
- ETL Processes. Experience with ETL tools and processes for effective data integration.
- SQL and NoSQL. Proficiency in both SQL and NoSQL databases to cater to diverse data storage needs.
- Programming. Knowledge of programming languages such as Python, Java, or Scala to support data processing and analysis tasks.
- Analytical Skills. Ability to analyze complex data requirements and design efficient, scalable solutions.
- Communication. Excellent communication skills to effectively collaborate with both technical and non-technical stakeholders, ensuring alignment on data strategies.