The question to ask before you build what someone asked for
Stakeholders request a solution. The decision underneath it is usually smaller than the thing they asked you to build.
Writing
Notes from the pipeline
Things I've learned building data platforms — what broke, what worked, and what the hype cycle gets wrong. New posts most months.
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Aug 24, 2026
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Aug 19, 2026
Writing a spec an engineer doesn't have to decode
A spec exists to remove the follow-up questions. The only honest way to find out whether it worked is to count them.
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Aug 14, 2026
The dashboard was wrong for six weeks and nobody noticed
A join quietly started dropping rows and the revenue dashboard kept looking plausible. What I changed so it never happens silently again.
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Aug 3, 2026
Semantic models are the most underrated work in analytics
Nobody puts "built a measure library" on a conference slide, but it took our reporting cycle from two days to four hours.
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Jul 22, 2026
Iceberg won. Now what?
Everyone agrees on the table format now. That settles much less than people think.
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Jul 9, 2026
What consolidating 8 source systems taught me about ELT design
Lessons from pulling product, marketing, and customer data into one Snowflake analytics layer without breaking anything downstream.
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Jun 25, 2026
dbt tests are unit tests for your beliefs
You think order_id is unique. The test is how you find out when you stop being right.
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Jun 18, 2026
What "done" means when the deliverable is a number
Software features have a demo anyone can judge. Data work ships a number, and "it looks about right" is how wrong numbers survive.
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Jun 12, 2026
DuckDB is my new scratchpad
Not everything needs the warehouse. A local engine that eats parquet has quietly changed how I debug and prototype.
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May 28, 2026
Cutting our Snowflake bill without touching a single dashboard
Full-refresh models were rebuilding the world nightly. Making them incremental cut warehouse compute hard, and nobody upstairs noticed a thing. That was the point.
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May 21, 2026
The dependency map nobody drew
Consolidating a lot of systems, the scary part was never a single pipeline. It was the graph of what breaks what, and which human owns each edge.
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May 15, 2026
The anomaly detector that cried wolf
My first risk model was technically excellent and practically ignored. Fixing it had nothing to do with the model.
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May 4, 2026
Data contracts: promising, mostly aspirational
The idea is right. The org chart is the hard part. Notes from trying a lightweight version in real life.
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Apr 20, 2026
BigQuery optimization is mostly about not being clever
How warehouse workloads got ~45% faster with partition pruning, honest data types, and the removal of my own smart ideas.
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Apr 14, 2026
What credit data taught me about data modeling
Financial data is audited, incentive-shaped, and unforgiving about "as of when." Two habits I picked up there and refuse to drop.
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Apr 8, 2026
Nobody reads your data docs. Write them anyway.
Documentation and lineage felt like chores until self-service went up 60% and my interrupt load collapsed. Turns out docs are read at exactly one moment.
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Mar 25, 2026
LLMs in the pipeline: where they actually help
Ignore the text-to-SQL demos. The wins are smaller, weirder, and mostly about unstructured inputs and terrible source data.
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Mar 12, 2026
From business analytics to data engineering: what actually transferred
I came in through the analytics door, not the CS door. Less of a handicap than the discourse suggests, with a couple of real gaps to close.
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Mar 5, 2026
Translation runs both ways. I was only good at one.
Everyone practices turning business needs into technical requirements. The return trip, explaining a constraint in terms someone actually cares about, gets almost no practice.
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Feb 27, 2026
Kicking the tires on Microsoft Fabric
A Snowflake-and-dbt person spends real evenings with Fabric and comes back with mixed, specific feelings.
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Feb 22, 2026
Boring pipelines are a feature
The most senior thing a data pipeline can do is nothing interesting. On idempotency, retries, and the luxury of not being needed at 3 a.m.