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Jordan Lewis

Data Platform Engineer · SF Bay Area

Jordan Lewis

I own the data stack, end to end.

I took a Dremio lakehouse from a single-VM proof of concept to a production-critical service at three nines: one SQL engine over 30+ sources across six backend types, used by about a dozen teams. Plus a Kafka platform, an LLM and MCP layer, and the on-call and HA/DR that keep it up.

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Jordan Lewis

Across the data lifecycle

  1. Data modeling & ETL
  2. Lakehouse & streaming platform
  3. Semantic layer
  4. Data products & APIs
  5. Analytics & BI
99.9%
Production lakehouse uptime
10+
Teams using the platform
30+
Data sources in one SQL engine
8
Platforms I run on Kubernetes

What I do

Platforms, end to end

I work across the whole stack that makes analytics possible: storage, query engines, streaming, identity, and governance.

Data lakehouse platforms

I run Dremio and an Apache Iceberg catalog on Kubernetes. One SQL engine queries HDFS, Hive, object storage, Snowflake, Postgres, and Mongo together, with a semantic layer, SSO, and query acceleration on top.

Reliability & operations

I own the platform end to end. Multi-environment CI/CD, on-call, incident response, HA/DR planning, and the dashboards that keep a production service at three nines.

Streaming & AI tooling

Kafka on Confluent for Kubernetes, with topics landing in the lakehouse as Iceberg tables. On top of it I build LLM and MCP tooling that documents a catalog and answers questions about it from your editor.

Selected work

Things I've built

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Writing

Recent posts

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Let's talk.

Happy to talk data platforms, lakehouses, or where AI actually earns its keep in infrastructure. LinkedIn is the fastest way to reach me.

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