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  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 database systems, especially when they’ve grown into a state where migrations, performance, or schema design have become limiting factors.

Recent work, using AI extensively:

- maintain a chat bot that can use psychometrics to adapt messages. - construct/evaluate a generic data warehouse based on deep knowlodge of AWS and DBMS

Weirly enough, I got an anthropic certification after all that.

Open to consulting or full-time roles where expertise on data is core to the business and performance/architecture matters.

Résumé: https://www.linkedin.com/in/eduardo-bellani/


This particular system is predicated on people actually doing the homework.

There were threats on 'cheating', but the system is failing at detecting the new 'cheating' mechanism.

I use quotes because what is being cheated at is the certification, not education. Mixing them into the same pipeline was always a mistake.

BTW: A tutor is a person. An AI is a search engine.


if you are searching for something similar but with more meat: https://ebellani.github.io/blog/2026/all-you-need-is-postgre...




your job page is dead, btw


  Location: Brazil (UTC-3, overlaps US hours)
  Remote: Yes
  Willing to Relocate: Yes (US preferred)
  Technologies: SQL Server, DBT, SQL Mesh, PostgreSQL, SQL, OLTP & OLAP, cloud optimization, query optimization, large-table migrations, F#, Clojure, Python, C#, C, Java, Ruby, Rust, Prolog, OCaml, Haskell
  Email: ebellani at gmail
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 think your post misses the point of the DBMS centralization: managed consistency.

It is not about ops cost in infrastructure, but ops cost in debugging consistency errors.


  Location: Brazil (UTC-3, overlaps US hours)
  Remote: Yes
  Willing to Relocate: Yes (US preferred)
  Technologies: SQL Server, DBT, SQL Mesh, PostgreSQL, SQL, OLTP & OLAP, cloud optimization, query optimization, large-table migrations, F#, Clojure, Python, C#, C, Java, Ruby, Rust, Prolog, OCaml, Haskell
  Email: ebellani at gmail
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.


  Location: Brazil (UTC-3, overlaps US hours)
  Remote: Yes
  Willing to Relocate: Yes (US preferred)
  Technologies: SQL Server, DBT, SQL Mesh, PostgreSQL, SQL, OLTP & OLAP, cloud optimization, query optimization, large-table migrations, F#, Clojure, Python, C#, C, Java, Ruby, Rust, Prolog, OCaml, Haskell
  Email: ebellani at gmail
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.



Wow, zooming out really puts the 2021-2022 hiring frenzy into perspective.


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.


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