Tu entrevista tecnica, en ingles

At BIT512 we had a storage failure that corrupted part of our document archive. I was the technical lead, so recovering it was on me. First I mapped exactly what was missing, file by file, instead of guessing. Then I rebuilt the ingestion pipeline and re-indexed the documents from the original sources. And I added integrity checks, so from that point on we could tell whether a document was complete or not. We restored the archive, and those checks are still running today. The same failure would now show up in hours, not weeks.

Por que sirve: Muestra que tomas responsabilidad y que dejas el sistema mejor de como lo encontraste.

At IncubApp we had to collect and process data from more than seventy five radio stations across the country. That was over ten million records, and the budget was small, so a server running all day was not an option. I designed a serverless architecture on A W S: Lambda for the processing, S3 for the raw files, and DynamoDB modeled around the access patterns we actually needed. I split the pipeline into small independent steps, so a failure in one station would not stop the rest. It handled the ten million records, and because it only ran when there was data, the cost stayed low.

Por que sirve: Aqui demuestras que piensas en costo y en fallas parciales, no solo en que funcione.

We had a search over four hundred and fifty thousand profiles and it was too slow to be useful. People were waiting seconds for results. I moved the search to OpenSearch, redesigned the index around how people actually searched, rewrote the queries, and added a ranking model on top. Queries came down to under fifty milliseconds, and ranking quality improved by about twenty five percent. The important part is that we measured it before and after, so it wasn't just a feeling.

Por que sirve: Cifras antes y despues. Es la respuesta que mas peso tiene en una entrevista tecnica.

Buho Labs. Online store owners can see that sales dropped, but not why. I wanted to build something that answers the why. I built it end to end on my own: the tracking script, the ingestion API on Cloudflare Workers, the database, the dashboard, and the deployment. It records what visitors do and turns it into plain language findings, in Spanish, for people who are not analysts. It is live with paying customers today. The hardest part was not the code, it was deciding what not to show: if a number cannot be backed by real data, it does not go on the screen.

Por que sirve: Cierra con la frase de honestidad de datos. Eso te separa de cualquier otro candidato.

I've been leading the technical side of a small team, and I've learned a lot, but I want to work at a bigger scale and with people I can learn from. I'm looking for a place where engineering standards are already strong.

I tend to go too deep into a problem before asking for help. I've been fixing that with a simple rule: if I'm stuck for more than an hour, I bring it to the team. It made me faster, and honestly it made the team faster too.

A teammate wanted to ship a feature that our data could not really support. Instead of arguing, I pulled the numbers and showed what we could and could not prove. We ended up shipping a smaller version that was honest. I've learned that data ends discussions faster than opinions.

I once shipped a change that looked fine locally and broke a report in production. I rolled it back within minutes, found the cause, and added a check so the same thing could not happen silently again. The lesson for me was that 'it works on my machine' is not verification.

I cut scope, not quality. I ask what the deadline really needs, ship that part properly, and I'm explicit about what is not included yet. In my last role we delivered a hundred percent of our milestones on time that way.

Still building, but with more architectural responsibility. I like being the person who can go from the database to the front end and keep the whole thing coherent.

dot NET Framework is the old one, Windows only. Modern dot NET, version five and up, is cross platform and open source. Today you would start a new project on dot NET eight.

It means a class does not create the things it depends on, it receives them. ASP dot NET Core has it built in: you register services in Program dot C S and the framework injects them into the constructor. There are three lifetimes: singleton, one for the whole app; scoped, one per request; and transient, a new one every time. It makes the code testable, because you can pass a fake one in a test.

Language Integrated Query. It lets you query collections or a database with chained methods. It is the same idea as filter and map in JavaScript: Where instead of filter, Select instead of map.

Value types like int, bool and struct are copied by value. Reference types like class, string and arrays are passed by reference. It is the same distinction as primitives versus objects in JavaScript.

First I would look at the execution plan instead of guessing. Usually it is a missing index, a function applied on an indexed column, or a query pulling far more rows than it needs. I would fix that, then measure again. I do not optimize anything I have not measured.

Authentication is proving who you are. Authorization is what you are allowed to do once you are in. Logging in is authentication; being able to delete a record is authorization.

Resources as nouns, HTTP verbs for the actions, and status codes that mean what they say. I validate the input at the edge, I never trust the client, and I keep write operations idempotent where I can, so a retry does not create a duplicate.

Not in one step. You add the new column first, deploy code that can handle both shapes, backfill the data, and only then remove the old one. The order matters: if the migration and the code go out in the wrong order, the app breaks in production.

Tests for the logic, and real verification for everything else. I run the build, I check the actual output, and for anything user facing I open it and look at it. I have learned not to say something is done until I have seen it working.

An index makes reads faster by keeping a sorted structure the engine can jump into. It costs you on writes, because every insert has to update the index too. So on a table that is written constantly, too many indexes will slow you down.