10+ years data engineering / platform architecture, including 4+ years hands-on Google Cloud Platform
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, Tenarai's 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.
Google Cloud Platform 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.
