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Jose Luis Ossio Bejarano

@joseluisossiobejaran

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Data Engineer at Real Men Apparel Company who built Snowflake pipelines and an Amazon Ads bid-management engine.

Bolivia

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At Real Men Apparel Company, I build and maintain production data pipelines in R and SQL, bringing Amazon, Shopify, TikTok Shop, and warehouse data into Snowflake. I also developed reconciliation and freshness monitoring, and delivered SQL and Power BI analyses for leadership.

As a consultant at X-Press Shapewear LLC, I built a Snowflake platform and a Python engine that automates Amazon Ads bid and budget changes. Over seven weeks, ad-attributed ACoS fell from 35% to 22% while ad spending dropped 30%; I also built customer behavior models for TIGO (Millicom) / Cabernet / Zanella that contributed to a 35% increase in average customer spend.

Experience

Work history, roles, and key accomplishments

Current

Data Engineer & Data Analyst

Current

Real Men Apparel Company

Jul 2023 - Present (3 years 3 months)

Build and maintain production ETL/ELT pipelines in R and SQL ingesting Amazon, Shopify, TikTok Shop, and warehouse data into Snowflake. Own day-to-day reliability of the production pipeline and deliver multi-channel SQL and Power BI analyses for leadership.

R SQL Snowflake ETL ELT API Integration Data Quality Power BI Amazon SP API Shopify TikTok Shop

Data Engineer Consultant

X-Press Shapewear LLC

May 2024 - Dec 2025 (1 year 7 months)

Designed and built the company's Snowflake data platform from scratch using a three-layer medallion architecture with RBAC, ingesting Shopify, Amazon, TikTok Shop, and Odoo data. Built automated reporting and a Python bid-management engine on the Amazon Ads API that reduced ACoS from 35% to 22% and raised ROAS from 2.9x to 4.6x.

Snowflake Medallion Architecture RBAC Python Ads APIs OAuth Shopify TikTok Shop Odoo Power BI Data Modeling ETL

Data Science Consultant

TIGO (Millicom) / Cabernet / Zanella

Nov 2021 - Jun 2023 (1 year 7 months)

Built customer behavior models (classification, XGBoost, grid-search tuning) that informed targeting decisions and contributed to a 35% increase in average customer spend. Segmented customers with K-Means, DBSCAN, and hierarchical clustering after full EDA.

Python XGBoost Classification K Means DBSCAN Hierarchical clustering EDA Machine Learning

Business Development Manager

ISOTEK SRL

Aug 2021 - Feb 2022 (6 months)

Designed Salesforce and Power BI dashboards for sales goals and annual forecasting, achieving a 17% revenue gain in the first quarter after rollout. Cut department response time by 50% with a task management system built on SharePoint, Salesforce, and automated workflows.

Salesforce Power BI SharePoint Workflow Automation Forecasting Dashboarding