Jessica Piñas

Development of AI-powered automation solutions using Python and machine learning in Azure and Databricks environments, supporting large-scale digital transformation initiatives.

Building scalable data ingestion, transformation, and cleaning pipelines in Databricks (Spark), preparing high-quality datasets for Retrieval-Augmented Generation (RAG) systems.

Designing and deploying end-to-end AI-based workflows to optimize data migrations and modernize legacy systems.

Fine-tuning open-source language models (LLMs) using QLoRA, utilizing virtual machines on Google Cloud Platform (GCP) for scalable training and deployment.

Design and optimization of extraction, transformation, and analysis processes for large volumes of data in BigQuery, enabling strategic data-driven decision-making for the application.

Development of interactive dashboards and reports in Power BI, defining and monitoring key KPIs and facilitating the communication of actionable insights to technical and business stakeholders.

Building and maintaining scalable data pipelines with DBT, applying best practices in modeling, testing, and documentation to ensure data quality and reliability.

Coordination and tracking of initiatives through Jira, collaborating closely with engineering and product teams in agile environments to align technical deliverables with business objectives.

• Performance evaluation and trend analysis of different projects through Power BI.

◦ Creation of dashboards and complex data models, using the DAX language.

◦ Design, development, and maintenance of metrics, reports, analyses, and dashboards to drive key business decisions.

• Data ingestion and extraction from various sources (MSQL server, Excel)

• Creation and monitoring of monthly and quarterly team KPIs.

• Recognition and adoption of best practices in reporting and analysis: data integrity, test design, validation, and documentation.