I play a key role in maintaining and optimizing the code that powers our data pipelines, specifically using PySpark. My responsibilities include ensuring the efficiency and validity of these pipelines, collaborating with team members to streamline processes.Additionally, I actively contribute to the preparation of analyses to validate Reinsurance data, collaborating closely with stakeholders. This involves using SQL and leveraging data visualization tools such as Palantir Foundry Countour to present insights in a clear and accessible manner.Furthermore, I contribute significantly to the development and management of a specialized tool designed for our stakeholders, collaborating with cross-functional teams. This tool facilitates the analysis of Large Corporate Risk, providing valuable insights for strategic decision-making.

• Integrating new data sources such as SAP Hana, SFTP, AWS S3, and Google APIs.• Performing data reloads, adding historical data, merging tables, and relocating tables using Databricks.• Preparing, validating, and transforming data to ensure its suitability for analytical purposes.• Developing Airflow (MWAA) DAGs, rescheduling coordinators, and linking workflows.• Implementing new robust and sustainable product features while improving existing ones.• Collaborating closely with the business to define solution requirements and identify key case studies to architect data solutions.

• Participated in a temporary educational project focused on learning and utilizing various technologies within the Azure ecosystem.• Developed Scala/SparkCore applications to process data efficiently.• Utilized SparkSQL to compute and visualize queries in Databricks Notebooks.• Gained experience in deploying Kafka to Azure Kubernetes Service (AKS) and using Kafka Connect to upload data from an Azure storage container.