I specialize in rescuing and scaling PostgreSQL systems that have become bottlenecks due to schema debt, growth, or operational complexity.
Recent work: re-architected two multi-terabyte OLTP tables (~2TB and ~1TB) handling 200+ writes/sec, improving scalability and reducing application-level complexity.
My work focuses on high-risk database migrations, dangerous schema remediation, hot-path optimization, and making existing systems scale without rewriting the product.
Open to consulting or full-time roles where data is central and performance matters.
I specialize in rescuing and scaling PostgreSQL systems that have become bottlenecks due to schema debt, growth, or operational complexity.
Recent work: re-architected two multi-terabyte OLTP tables (~2TB and ~1TB) handling 200+ writes/sec, improving scalability and reducing application-level complexity.
My work focuses on high-risk database migrations, dangerous schema remediation, hot-path optimization, and making existing systems scale without rewriting the product.
Open to consulting or full-time roles where data is central and performance matters.
Sort of, that it crosses so many lines makes it seem like it must be 6X, but it peaks at 230 based on a baseline of 100, so just 2.3X their baseline. Still a ton, but not as much as I thought at first glance.
The "edit graph" button reveals some pretty sweet ways to mess with the chart, yet I don't see an option to fix the Y axis at zero. Weird.
Maybe words work better?
There were roughly 28 months' worth of tech job postings within the 15 month period from July 2021 to October 2022.
If you change the baseline to a rough average of the last 2 years, 0.66, that ratio becomes 42 months' worth of job postings within 15 months.
I'd be curious to see what the numbers look like as a percentage of the existing tech workforce. Like, if there are 100 workers and the number of job postings doubled from 5 to 10, that's a huge deal. But if there are 1000000 workers and the number of job postings doubled from 1 to 2, well that's not a huge deal.
> The Agile example makes this worse, not better. Yes, Agile was overhyped and badly implemented in many places. But using that to indict the entire movement as Girardian ritual is precisely the logical move the author claims to be critiquing: take some real failures, blame them on a paradigm rather than specific implementations, declare the whole thing rotten. He scapegoats Agile to validate his theory about scapegoating
I don't think the author did that at all. He was fair to interactive development. He specifically points out the scapegoating of waterfall, where the methodology was misrepresented in order to create the space for agile.
Location: EST
Remote: Yes
Willing to relocate: Yes (US preferred)
Technologies: PostgreSQL (partitioning, performance, OLTP architecture), SQL, F#, C#, C, Java, Clojure, Common Lisp, Scheme, Emacs Lisp, Python, Ruby, AWS, Linux
Email: ebellani at gmail
I work on high-throughput systems, especially when they’ve grown into a state where migrations, performance, or schema design have become limiting factors.
Recent work:
Re-architected two multi-terabyte OLTP tables (~2TB and ~1TB) receiving 200+ writes/sec. I focus on “rescue architecture” work: fixing dangerous schemas, stabilizing hot paths, removing app-level complexity, and making Postgres scale without rewriting the product.
Open to consulting or full-time roles where data is core to the business and performance/architecture matters.
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