- Develop scalable and efficient data pipelines to attend data visualization requirements using python and SQL.- Monitor and troubleshoot data pipelines (AWS) to maintain data availability and reliability.- Document data processes, data flows, and architectural decisions for reference and knowledge sharing using Github and Azure DevOps.- Develop standard SQL queries responsible for implementing business rules on the data.- Develop dashboards in Tableau, Looker and Power BI.- Collaborate with business stakeholders to understand and translate business.- Provide technical leadership to the data management team to ensure high-quality work.Technologies: Cloud GCP | Python | ETL | SQL | Oracle | Data Modelling | BigQuery | Airflow | DataFlow | Domino Datalabs | Databricks | AWS Glue, | AWS S3 | GitHub | CI/CD | Tableau | Spotfire | Amazon RDS | AWS Athena | Azure DevOps.

- Manage multiple squads, ensuring cross-functional collaboration and alignment with objectives using agile and scrum methodologies.- Communicate data analysis results and insights to different audiences.- Provide technical leadership to the data science and analytics team.Technologies: Cloud GCP | Domino | SQL | Python | Braze | Looker | DataStudio | API | BigData | Gitlab | Airflow | Data Warehousing | Data Governance | Agile | Scrum.

- Collect, clean, process, and analyze large datasets to identify valuable insights and trends.- Work closely with stakeholders to understand their needs and provide valuable data solutions.- Evaluate different solutions and approaches to Data Science problems and select the best options.Technologies: JIRA | Cloud GCP | Domino | SQL | Vertica | Python | Braze | Looker | DataStudio | API | BigData | Gitlab | Airflow | Data Warehousing | Clusterization | Regression | Classification | Customer Experience Reports.

- Data collection and apply statistical and mathematical techniques for product development screening (ANOVA, Mixed Models, A/B Testing) and exploratory data analysis using software R. - Conducted trials, designing experiments and randomization strategies to assess and optimize data analysis algorithms and machine learning models: regression, classification and clusterization. - Collaborated with stakeholders and operational teams to align activities and create processes to improve efficiency in data collection, analysis, and reporting. - Provide technical leadership to the team and delivering training and guidance.Technologies: R Project| SAS | SQL | LIMS | Project Management.