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$ whoami
Forward Deployed Engineering · Applied Engineering

Richie Bachala

Sr. Manager, Applied Engineering @ Snowflake

I help enterprises get AI agents into production on data they can trust.

I lead Applied Engineering for US West customers at Snowflake, contribute to open-source Iceberg, and run hands-on agent workshops in the Bay Area. I'm writing AI-Based Data Engineering.

Petabyte Platforms·Interoperability·AI Agents in Production
linkedinmediumgithub
Richie Bachala

Focus areas

agents
Agentic AI in production

Production deployments across Majors US-WEST.

databases
Every generation of data infrastructure

Oracle, YugabyteDB, Snowflake. Iceberg, Polaris, and Ossie SME.

gtm
The SE leader who's been the buyer

Formerly Director of SE, North Americas at Yugabyte, $56M quota.

ship outcomes
Built once, shipped everywhere

Platform IP designed to scale past one team, from first deployment to renewal.

Now updated Oct 2026

$ richie --now
nextKeynote, Bring Your Own Model · techequity ai summit · nov 4 · register
lastSnowflake Bay Area User Group · oct 6 · menlo park
writingAI-Based Data Engineering · packt · 14 chapters
shippedpg_lake 3.5, universal Iceberg REST catalog · write-up

Talks all talks

Richie presenting The Arc, Foundation to Intelligence series, at TechEquity AI Forum
"The Arc," Foundation to Intelligence series. TechEquity AI Forum, Sep 29, 2026
2026-11-04Keynote: Bring Your Own Model, the case for open weights and open choicenextTechEquity AI Summit, Fall 2026 · Snowflake Silicon Valley AI Hub, Menlo Parkspeakers & registrationannouncement
2026-10-06Build a Production AI Agent with Snowflake CoCoSnowflake Bay Area User Group, Menlo Park, with Shayak Sen, CoCo Engineering Leadevent page
2026-09-29From One Agent to Many: Multi-Agent Orchestration with CoCoTechEquity AI Forum, Menlo Parkwatchevent page
2026-08-20Foundation to Intelligence, Level 3: Cost IntelligenceTechEquity AI Forum, Menlo Parkwatchevent pagerecap

Book details

AI-Based Data Engineering cover

How to build data platforms AI agents can trust, from context pipelines to evals and governance. The case study starts at an AI‑readiness score of 4/18 and ends at 18/18.

Packt, 2026 · pre-order · score your platform · code

Readiness score your platform

$ readiness --platform opspulse
dimensionch 1ch 14
D1 schema freshness██████3/3
D2 semantic coverage██████3/3
D3 test coverage██████3/3
D4 eval readiness██████3/3
D5 governance scope██████3/3
D6 lineage coverage██████3/3
total4/1818/18

Writing all writing

eng blogpg_lake 3.5: Universal Postgres Iceberg REST CatalogPostgres attaches to any Iceberg REST catalog, including Polaris, Lakekeeper, and NessieOct 2026 builders blogSnowflake & Databricks Interoperability, a five-part seriesFrom eight write-once, read-many patterns to CLD with Cortex AI5 parts eng blogSnowflake Horizon vs. Databricks Unity CatalogGovernance compared: discovery, lineage, access control2026

Open source all projects

pg_lakeREST catalog base URI, /v1/config prefix detection, unauthenticated catalog accessSnowflake-Labs · 13 merged, 2 in review iceberg-goCatalog conformance suite: table lifecycle, cross-namespace rename, and commit conformance; external REST catalogs in CIApache Iceberg · 5 merged blueprintBlueprint Manager, co-createdSnowflake-Labs · announced at Snowflake Summit 2026 icebergAdded Snowflake Horizon Catalog to the Iceberg compatibility matrixicebergmatrix.org · 6 merged

Guest book signed on x

$ sign