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Build an automated CI/CD evaluation pipeline for multi-agent systems on Google Cloud using Vertex AI EvalTask, Google ADK, and GitHub Actions.
Build a production-ready multi-agent travel concierge on Google Cloud using Google ADK, the Supervisor pattern, MCP tool boundaries, and BigQuery.
A production guide to bootstrapping Offvia, an AI travel concierge on Google Cloud: bypassing weeks of IAM red tape, Express Mode, and Pydantic v2 data contracts.
Build a production-ready GCP data orchestration layer with Managed Service for Apache Airflow, Cloud Workflows, Dataform, and BigQuery.
Build a production BigQuery Medallion Lakehouse with Google Cloud Dataform: incremental SQLX models, late-arrival deduplication, quarantine tables, assertions, and release workflows.
Build a reliable BigQuery transformation layer with Medallion architecture, Dataform or dbt, incremental processing, deduplication, and practical data-quality controls.
Build a resilient GCP streaming pipeline with Pub/Sub, Apache Beam on Dataflow, raw-event landing, quarantine handling, event-time windows, and BigQuery Storage Write API sinks.
A practical guide to choosing between Pub/Sub BigQuery subscriptions, Dataflow, the BigQuery Storage Write API, and batch loads—without over-engineering the path.
A practical, end-to-end GCP data engineering lab covering Cloud Storage, BigLake external connections, partitioned and clustered BigQuery, materialized views, Time Travel, and authorized views.
A step-by-step architectural guide to core Google Cloud data engineering storage and access primitives. From Cloud Storage to partitioned BigQuery, materialized views, and authorized views.
