Google Data Platform Architect

10 years data engineering / platform architecture including 4 years hands-on GCP

• Own the end-to-end target architecture across ingestion raw conformed and consumption layers and maintain it as new sources are onboarded.

• Define the source onboarding pattern and extend it to new systems working with client teams and third-party system integrators who own those systems.

• Govern Pub/Sub schemas as enforced data contracts including evolution and versioning policy across independently owned sources.

• Own the streaming correctness design: ordering idempotency exactly-once semantics dead letter queues and an operator-usable replay and reprocess mechanism.

• Own the Dataform architecture across conformance and aggregation the assertion-based data quality approach and the dimensional model for business-ready marts.

• Design the governance and security model: Dataplex zones IAM policy tags column- and row-level security VPC Service Controls CMEK and DLP coverage.

• Own BigQuery and Dataflow cost architecture including the always-on streaming footprint.

• Lead the implementation of QUIVER Tenarais DataOps accelerator monitoring across Pub/Sub backlog Dataflow lag Dataform assertions and BigQuery telemetry; Dataplex-integrated governance; self-healing patterns with explicit escalation boundaries; and cost attribution by data product.

• Secure client architecture security and privacy approvals; mentor the delivery pod and enforce standards through review.

• Proven experience architecting event-driven streaming platforms not batch ETL scaled up Pub/Sub Dataflow / Apache Beam and the operational realities of always-on streaming.

• Command of streaming correctness: ordering idempotency exactly-once late and duplicate events dead letter and replay design.

• Deep BigQuery expertise modeling tuning partitioning and clustering reservations cost optimization.

• Dimensional modeling depth: facts dimensions conformed dimensions across domains.

• Dataform or equivalent in-warehouse transformation framework with dependency management and assertion-based quality.

• Dataplex DLP and fine-grained BigQuery access control.

• Experience integrating enterprise SaaS systems as event sources and their change-event mechanisms.

• Strong SQL and Python; Terraform; CI/CD for data pipelines.

• Ability to run technical review with enterprise architects and security teams and defend design decisions.

• GCP Professional Data Engineer or Professional Cloud Architect certification.

• Public sector or regulated-industry delivery experience.

• Analytics Hub and Looker / LookML; DataOps or observability tooling; Vertex AI and MLOps exposure.