Extract, transform, and load Salesforce data cleanly, whether you're moving one legacy system in or consolidating 10+ TB across a dozen orgs. Built on Bulk API 2.0 and proven ETL tooling, with a record-level audit trail you can hand to an auditor.
ETL sounds simple until a field type shifts, a lookup breaks, or history goes missing. Here's how each move actually gets handled.
Pull every record, attachment, field, and history item out of the source. Bulk API 2.0 with async and batch patterns and partitioning keeps it fast at extreme data volume, without hammering governor limits.
Map and reshape data for the destination model. Field mapping, type conversion, deduplication, and reference integrity all get validated before a single record loads.
Write to the target with checkpoints and resume. If a quality gate fails, the run stops instead of shipping bad data. You fix the issue, re-run, and every record lands clean.
The right tool for the job, from Bulk API pipelines to full iPaaS, tuned for large data volume and steady performance.
Moving off an old CRM, database, or homegrown system into Salesforce, including messy source data and custom schemas.
Migration services →Consolidating or separating data across Salesforce orgs after a merger, acquisition, or reorg, with data residency handled across the US, EU, and APAC.
Multi-org work →Pulling a full copy of your Salesforce data out so you keep control of it, independent of any vendor.
Exit services →Landing Salesforce data into Snowflake or Redshift for reporting, with pipelines built on Workato, FiveTran, or custom code.
Org audit →You work directly with Tyler Colby, a Salesforce Certified Data Architecture and Management Designer with more than 20 years in the ecosystem and a focus on data migration. Past work spans Fortune 10/100 and regulated companies, plus nonprofits like St. Jude Children's Research Hospital and the Houston Food Bank. More about the practice.
Extracting data from a source, transforming it to fit the Salesforce data model, and loading it in (or extracting out of Salesforce for an exit or warehouse). It covers field mapping, type conversion, deduplication, reference integrity, and validation. At scale it leans on Bulk API 2.0 and async, batch, and partitioning patterns.
For large data volume work up to 10+ TB, the approach uses Bulk API 2.0, async processing, partitioning, and archiving to keep performance steady. Runs are checkpointed so they can resume, and every record is validated against quality gates before it lands.
No. The tooling runs entirely on your own hardware. There's no shared cloud backend and no data egress, so your data never enters the vendor's chain of custody. Your auditor can verify the audit chain on their own machine.
Yes. Multi-org consolidation driven by mergers and acquisitions is a repeatable pattern here, both splitting one org into several and merging several into one, including data-residency migrations across the US, EU, and APAC.
Tell me the source, the target, and the rough data volume. I'll tell you how I'd approach it.