Summary
What you’ll impact
The Principal Cloud Data Architect will lead the design and implementation of large-scale data ecosystems on a cloud platform, defining strategy, building self-serve platforms, and overseeing migrations. The role requires extensive IT experience, deep expertise in the cloud platform, and strong leadership to manage cross-functional teams and ensure data governance and security.
Responsibilities
What you'll do
- Strategic Architecture: Define the long-term roadmap for data platforms on GCP, ensuring alignment with global business goals and "North Star" data strategies.
- Self-Serve Platform Design: Architect and oversee the build-out of modern, self-serve data architectures that empower decentralized teams while maintaining central standards.
- Large-Scale Migrations: Lead complex end-to-end migration from AWS to GCP.
- Data Governance & Security: Design and enforce robust data security frameworks including IAM, VPC Service Controls, Data Masking/Encryption, and automated governance using Dataplex.
- Infrastructure as Code (IaC): Drive automation using Terraform or Pulumi to ensure repeatable, scalable, and version-controlled infrastructure.
- Executive Stakeholder Management: Act as a trusted advisor to the VP of Data, articulating the ROI of data initiatives and managing technical risk.
Requirements
What you’ll bring
- 16–20 years of overall IT experience.
- 5–6 years of recent, hands-on experience with GCP.
- Proven experience working on Google Data projects.
- Valid and recent GCP certification.
- Cloud Expertise: Expert-level mastery of the GCP Data Stack:
- Storage & Warehouse: BigQuery (including BigLake and Omni), Google Cloud Storage.
- Processing: Dataflow (Apache Beam), Dataproc (Spark/Hadoop), Cloud Composer (Airflow).
- Messaging: Pub/Sub and Confluent/Kafka integration.
- Analytics & AI: Looker, Vertex AI, and BigQuery ML.
- Certifications: Must hold an active GCP Professional Data Engineer certification.
- DRP ID Performance: A Data Readiness Placement (DRP) ID with a verified score of 50+ is highly preferable, demonstrating a high level of technical proficiency and architectural maturity.
- Modern Data Stack: Deep experience with dbt, Airflow, and containerization (GKE/Kubernetes).
- Years of Experience: 16–20 years in Data Engineering, Data Warehousing, and Business Intelligence, with at least 6+ years focused specifically on GCP.
- Migration Track Record: Proven experience leading at least two enterprise-scale migrations (PB-scale) to the cloud.
- Leadership: Demonstrated experience leading large, cross-functional engineering teams in an Agile/DevOps environment.
- Education: Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related technical field.