GCP Database and ETL Expert

I run several workloads on Google Cloud and need a hand tightening up the data layer and the pipelines that feed it. The stack relies on BigQuery as the analytics warehouse and Redis as a high-speed cache / serving store. My immediate priorities are:

• BigQuery – review table design, partitioning and clustering strategies, then tune query performance so nightly reports complete within their SLA.
• Redis – streamline bulk imports, refine caching logic, and ensure data is served with sub-millisecond latency under peak traffic.
• ETL – overhaul the transformation stage of an existing Dataflow pipeline; the extract and load pieces are fine, but the current transforms are brittle and expensive.

Alongside the above, everything must follow best practices for Secrets Manager and IAM so credentials stay out of code and service accounts have the least-privilege they need.

Acceptance is straightforward: dashboards show the new query runtimes, Redis latency sits below our target, and the transformation job runs error-free with costs logged in Cloud Monitoring.

If you’re comfortable jumping between BigQuery optimisation, Redis internals, and Dataflow transforms—while keeping security locked down—this should be a focused, satisfying engagement.