Led the implementation of the company's digital transformation process, focusing on data governance, DataOps, Analytics, and Advanced Analytics.Extensively utilized the Google Cloud Platform (GCP) Data Stack, leveraging key tools such as BigQuery, Cloud Functions, Airflow, Dataflow, Pub/Sub, and Git for code versioning (BitBucket + CI).Created and managed end-to-end ETL processes within the Data Lakehouse architecture, employing SQL and Python as primary languages. Developed data models to support consumption in Looker Studio and Metabase across all departments, ensuring comprehensive documentation and robust data management practices.Orchestrated data ingestion from transactional databases, employing hybrid platforms and conducting Change Data Capture (CDC) proofs-of-concept for seamless integration with BigQuery. Structured alternative ingestion methods to optimize data flow into BigQuery, aiming to establish a scalable and well-documented Analytics environment.Working with stack AWS + Trino + DBTExtras Works: Testing Snowflake Environment, Working on GCP + AWS Certifications

Served as a data engineer specializing in the development of Datalake and Business Intelligence (BI) solutions tailored to the healthcare sector. Collaborated on planning, defining business rules, and implementing innovative actions for SulAmérica's telemedicine initiatives.Utilized the Google Cloud Platform (GCP) Data Stack, leveraging key BigData tools such as BigQuery, Cloud Functions, Airflow, and the Git code versioning system (BitBucket + Jenkins CI).Spearheaded the creation and management of the end-to-end ETL process within the Datalake House concept, adhering to data governance protocols outlined in the DAMA-DMBOK Framework. Primarily employed SQL and Python to model data, ensuring seamless consumption in Looker Studio for the entire telemedicine domain.Assumed responsibility for ingesting data from diverse NoSQL databases, such as Firebase, Datastore, and MongoDB (DocumentDB), into BigQuery. Effectively structured and transformed information from unstructured fields, ensuring accurate representation within the analytics environment.Conducted statistical metrics evaluation and customer segmentation initiatives to inform targeted marketing strategies, optimize business operations, and enhance performance in the healthcare sector. Leveraged diverse data sources, applied advanced analytical techniques, and developed optimization functions to drive operational efficiency and improve business processes.

I developed Business Intelligence (BI) solutions focused on People Analytics as a Data Anlytics Engineer. I collaborated on planning, defining business rules, and implementing innovative actions for the human resources area.I utilized the Google Cloud Platform (GCP) Data Stack - including BigQuery, Kubernetes, Docker, API Engine, and Cloud Functions, to handle with Big Data paradigm.I led end-to-end ETL process using SQL and Python, transforming and modeling data for consumption in Power BI, in partnered with DataViz to create comprehensive Dashboards, integrating metrics and overseeing data processing. Managed Power BI Workspace, programmed executions, and implemented security rules such as Row-Level Security (RLS) Filter for public-facing applications.I employed machine learning and Natural Language Processing (NLP) algorithms to analyze employee feedback during the COVID-19 era, extracting meaningful insights.I implemented Natural Language Processing techniques and embraced MLOps principles, combining data ops and ML Engineer concepts to optimize machine learning workflows.

I developed dashboards and analytics processes using industry-leading Business Intelligence Software QlikSense and QlikView - such as Power BI, and Tableau.I built and maintained the end-to-end creation of ETL processes, leveraging SQL language embedded within Qlik Platforms. Data modeling emerged as a prominent skill, underscoring its significance throughout my career. Additionally, I specialized in building KPIs, defining business rules, and conducting analyses specific to the pharmaceutical industry. My experience encompasses a wide range of pharmaceutical industry audits, including nDDD, CUP, Audit, GPS, PMB, MDTR, and MI.I handled various data sources, frequently receiving working files in FLAT FILES from reputable providers like IQVIA or CloseUP. Additionally, I seamlessly integrated structured databases such as SQL Server and other sales control databases from client sources.Leveraged Alteryx Platform for data manipulation when necessary. Demonstrated versatility by spearheading a responsive Chatbot project utilizing QlikSense Server Engine, Python, and frameworks like RASA-NLU and Diagram Flow.