Senior Data Architect- GCP

Role & responsibilities

• Design and implement scalable, secure, and cost-effective data architectures using GCP.
• Lead the design and development of data pipelines with BigQuery, Dataflow, and Cloud Storage.
• Architect and implement data lakes, data warehouses, and real-time data processing solutions on GCP.
• Ensure data architecture aligns with business goals, governance, and compliance requirements.
• Collaborate with stakeholders to define data strategy and roadmap.
• Design and deploy BigQuery solutions for optimized performance and cost efficiency.
• Build and maintain ETL/ELT pipelines for large-scale data processing.
• Leverage Cloud Pub/Sub, Dataflow, and Cloud Functions for real-time data integration.
• Implement best practices for data security, privacy, and compliance in cloud environments.
• Integrate machine learning workflows with data pipelines and analytics tools.
• Define data governance frameworks and manage data lineage.
• Lead data modeling efforts to ensure consistency, accuracy, and performance across systems.
• Optimize cloud infrastructure for scalability, performance, and reliability.
• Mentor junior team members and ensure adherence to architectural standards.
• Collaborate with DevOps teams to implement Infrastructure as Code (Terraform, Cloud Deployment Manager).
• Ensure high availability and disaster recovery solutions are built into data systems.
• Conduct technical reviews, audits, and performance tuning for data solutions.
• Design solutions for multi-region and multi-cloud data architecture.
• Stay updated on emerging technologies and trends in data engineering and GCP.
• Drive innovation in data architecture, recommending new tools and services on GCP.

Preferred candidate profile

• 7+ years of experience in data architecture, with at least 3 years in GCP environments.
• Expertise in BigQuery, Cloud Dataflow, Cloud Pub/Sub, Cloud Storage, and related GCP services.
• Strong experience in data warehousing, data lakes, and real-time data pipelines.
• Proficiency in SQL, Python, or other data processing languages.
• Experience with cloud security, data governance, and compliance frameworks.
• Strong problem-solving skills and ability to architect solutions for complex data environments.
• Google Cloud Certification (Professional Data Engineer, Professional Cloud Architect) preferred.
• Leadership experience and ability to mentor technical teams.
• Excellent communication and collaboration skills.