I prepare, validate and organize information into useful files and reports. I work with Python, SQL, Excel and Power BI, paying attention to business rules and data quality.
I am looking for remote data and reporting roles, as well as freelance file-cleaning, SQL export and ETL consolidation projects.
Three small demonstrations of the process, deliverables and limitations. These are not client projects.
01Demonstration · fictional data
Excel & CSV cleaning
A clean file with clearly recorded exceptions.
8 rows checked
Sales records with inconsistent formats, duplicates and invalid amounts.
View process and checks
Process and rules
Normalize text and decimal commas; validate amounts and categories; keep the first valid ID. Ambiguous data is separated, not invented.
Deliverables
Clean CSV, rejected records with their source row and a validation summary. Original file preserved.
Validation
8 rows = 4 valid + 3 rejected + 1 duplicate. Reconciled total: 185.50, without a real currency.
PDF in Spanish
02Demonstration · fictional data
SQL-to-file export
A verified export that leaves source records unchanged.
3 orders exported
Export only confirmed orders and verify that the file matches the query.
View process and checks
Process and rules
Parameterized query, ID ordering and UTF-8 CSV. Amounts stored in cents and formatted on export.
Deliverables
Structured CSV, query and row-count and amount checks. Confirmation that the database did not change.
Validation
3 orders exported, 1 excluded by status and a verified total of 150.00. Local SQLite example.
PDF in Spanish
03Demonstration · fictional data
ETL consolidation
Two consolidated batches without duplicating the second load.
0 new records on rerun
Combine movements from two batches, detect repeated records and separate unknown customers.
View process and checks
Process and rules
Validate customers against a catalog and check unique IDs. An existing ID with different content needs an agreed update policy.
Deliverables
Consolidated table, CSV export and counts of accepted, repeated and rejected records per run.
Validation
First load: 4 new, 1 repeated and 1 rejected. Second: 0 new, 5 repeated and 1 rejected.
PDF in Spanish
Before starting, we agree on sources, volume, quality rules, output format, access and timeline. Scope is confirmed for each project.
Professional background
Work experience
Data assistant with AI
La Fortuna S.A. / Acertemos
–
Cali · Fixed-term employment and SENA practical placement
Supported operational Power BI reports by downloading, reviewing and loading information.
Developed and adjusted Python and pandas scripts to download, transform and consolidate files.
Contributed to consolidating reports in PostgreSQL through tables, SQL queries and ETL processes.
Reviewed duplicates, incremental loads and execution errors; documented processes and tested n8n and Docker.
Tools used
Python
pandas
SQL
PostgreSQL
Excel
Power BI
ETL
SENA
Training
Languages
Native Spanish.
English: reading and conversational comprehension, with functional spoken communication. No certified proficiency level.
2025–2026
Data Processing for Artificial Intelligence Models
SENA
Technical training and practical placement completed. Diploma pending issuance.
2020
Technical training in Computer Systems
SENA
Program passed, as documented in the assessment certificate.
2025
Database Development with SQL
SENA
Approved competencies documented; not presented as a final course diploma.
2025
Variables and Control Structures in Python
SENA · 48 h
December 2025.
2026
Implementation of Artificial Intelligence Solutions
SENA · 48 h
July 2026.
Learning & collaboration
Academic projects
Practical learning with team contributions and explicit limitations.
Bird data in Cali
A collective SENA project. I contributed to preparing audio records, organizing data and generating spectrograms. The geographic exploration shows the team's curated evidence; it is not an identification system validated for production.
383 curated records · 54 main species · 312 unique locations
A subset of 542 original rows, with 159 documented exclusions. External taxonomic review pending.
Speaker at the Biodiversity Data Hackathon, RUPIV · 3 October 2025.
Explore the project map
Financial data transformation
An academic project to transform payment records into CSV, organize PostgreSQL layers and record data loads. It is not attributed to my La Fortuna employment.
Image exploration
An academic prototype with image uploads and a gallery, visual processing and K-Means and SSD experiments. A learning project, not a finished commercial product.
Employment & freelance projects
Let's talk about the work
For a remote role or a data project, email me with the goal, available files or sources and the result you need. Please do not send sensitive data in your first message.
