I’m looking for someone who has already moved Microsoft SSIS workloads into Google Cloud and can guide me through a clean, production-ready rebuild of our existing pipelines. Right now the jobs pull from a mix of relational databases and nightly flat-file drops; the goal is to land everything in BigQuery with the same—or better—performance, data quality, and monitoring we have today. Here’s what I need from you: • Assess the current SSIS packages, map out every source table and file feed, and document the equivalent flow on GCP. • Design and build the new pipelines using native services (Dataflow, Cloud Data Fusion, Cloud Composer, or any combination you feel is best) with full error handling, logging, and retry logic. • Automate scheduling and environment-specific configuration so deployments to dev, test, and prod are effortless—Terraform or Deployment Manager scripts are welcome. • Provide hand-over documentation plus a short walkthrough so my team can operate and extend the solution. You should be comfortable optimizing BigQuery schemas and partitioning strategies, securing data with IAM and service accounts, and ensuring that both the database feeds and the flat-file loads arrive in BigQuery in a consistent, auditable state. If this sounds like your kind of project, tell me briefly about a similar migration you’ve completed, the GCP tools you prefer for the extract and load stages, and how you’d structure the hand-over. I’m ready to start as soon as we agree on the best approach.